359 Interpretability Jobs

As a Generative AI Developer at our company, you will be responsible for building cutting-edge generative models to create innovative, human-like content across various domains such as natural language generation, image generation, and more. Your expertise in machine learning, deep learning, and natural language processing will be crucial for developing AI systems that utilize generative models like GPT, GANs, VAEs, and other neural networks. **Key Responsibilities:** - Develop and fine-tune generative models using techniques like GANs, VAEs, Transformers, and Diffusion models. - Work on tasks including text generation, image generation, music/sound generation, video creation, and other creative AI applications. - Design, build, and deploy models using frameworks like TensorFlow, PyTorch, Hugging Face, OpenAI's GPT, or similar tools. - Optimize AI models for performance, accuracy, and scalability in real-world production environments. - Research and stay updated on the latest trends, papers, and breakthroughs in generative AI. - Collaborate with other teams to integrate models into production systems. - Work on data preprocessing, augmentation, and designing pipelines to ensure high-quality input for model training. - Document your code, process, and model outputs for team-wide visibility and knowledge sharing. **Qualifications Required:** - Bachelor's or Master's degree in Computer Science or related fields. - 3-4 years of hands-on experience in developing Generative AI solutions. - Strong understanding of deep learning algorithms, especially in generative models like GANs, VAEs, Diffusion models, or large-scale language models like GPT. - Hands-on experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or Hugging Face. - Experience working with neural networks, unsupervised learning, and NLP. - Strong programming skills in Python, including deep learning libraries. - Familiarity with cloud platforms (AWS, GCP, or Azure) for model training and deployment. - Strong mathematical and statistical knowledge, particularly in probability theory, linear algebra, and optimization. - Experience in large-scale model training, fine-tuning, or distributed computing. - Knowledge of reinforcement learning and self-supervised learning. - Familiarity with AI ethics, bias mitigation, and interpretability in generative models.,

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. You will work closely with Product Owners and Development teams to lead the design efforts and come up with implementation strategy for AI solutions for CPG integrated Marketing department. Primary Duties And Responsibilities Lead the development and deployment of AI-enhanced BI solutions across cloud platforms. Build and optimize data pipelines, models, and dashboards for real-time insights. Collaborate with architects and stakeholders to ensure alignment with business goals. Implement MLOps practices for continuous integration and delivery of ML models. Ensure compliance with data governance, privacy, and security standards. Mentor junior developers and foster a culture of innovation and excellence Required Education, Experience And Skills Data Engineering Strong experience in data modeling, ETL pipeline design, and orchestration. Proficient in Apache Spark, Databricks, Airflow, Kafka. Advanced SQL skills and experience with Snowflake, BigQuery, or Redshift. Cloud Platforms Hands-on with Azure Data Factory, AWS Glue, or GCP Dataflow. Solid grasp of cloud-native architecture and cost optimization strategies. Machine Learning & AI Experience across the ML lifecycle: data prep, training, deployment, monitoring. Familiarity with Azure ML, SageMaker, or Vertex AI. Understanding of model interpretability, bias detection, and data drift. Python programming Data Governance & Security Knowledge of GDPR, CCPA, and enterprise data privacy frameworks. Experience with data lineage, cataloging, and access control mechanisms MLOps & CI/CD Skilled in MLflow, Kubeflow, GitHub Actions, Terraform. Automating model deployment and monitoring pipelines. 🤝 Soft Skills & Leadership Strong ability to translate business needs into technical solutions. Clear communicator who can explain AI/ML concepts to non-technical stakeholders. Collaborative mindset to work with data scientists, engineers, and business teams. Strategic thinker with a focus on ROI, feasibility, and data readiness. Change leader who promotes AI literacy and manages organizational adoption. Preferred Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, or related field. 5+ years of experience in data engineering, BI development, or AI solution delivery. Certifications in cloud platforms or ML tools are a plus. Python Programming About Micron Technology, Inc. We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all . With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® and Crucial® brands. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities — from the data center to the intelligent edge and across the client and mobile user experience. To learn more, please visit micron.com/careers All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. To request assistance with the application process and/or for reasonable accommodations, please contact hrsupport_india@micron.com Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards. Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron. AI alert : Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification. Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.

Role Overview We are seeking a Machine Learning Engineer to join a high-impact team within Experian Consumer Services (ECS) , focused on building scalable, reusable AI capabilities that power personalized financial experiences for millions of users. This role is ideal for someone who thrives at the intersection of machine learning, software engineering, and product thinking . You will work closely with product managers , data scientists , platform engineers , and UX teams to understand consumer needs, define ML-driven solutions, and deliver production-grade AI services such as LLM-as-a-Service , enterprise knowledge orchestration , predictive intelligence APIs , and personalized decisioning engines . Success in this role requires not only strong technical skills but also the ability to evaluate trade-offs , select the right models and tools , and align ML solutions with business goals . You’ll be expected to own the full ML lifecycle—from problem framing and experimentation to deployment, monitoring, and continuous improvement. Key Responsibilities 1. Business-Aligned ML Engineering Collaborate with product and analytics teams to identify high-impact personalization and automation opportunities. Translate business problems into ML use cases, selecting appropriate modeling techniques (e.g., classification, ranking, recommendation, summarization). Evaluate trade-offs between accuracy, interpretability, latency, and scalability to guide model and architecture choices. 2. Model Development & Optimization Design and implement ML models using Python and frameworks like scikit-learn , XGBoost , TensorFlow , and PyTorch . Apply advanced techniques such as feature selection , regularization , hyperparameter tuning (Grid Search, Bayesian Optimization), and ensemble learning . Leverage transfer learning , fine-tuning , and prompt engineering to extend the capabilities of pre-trained LLMs. 3. LLM Integration & Extension Build and operationalize LLM-based services using Amazon Bedrock , LangChain , and vector databases (e.g., FAISS, Pinecone). Develop use cases such as intelligent summarization, contextual recommendations, and conversational personalization using retrieval-augmented generation (RAG) pipelines. 4. Productionization & Deployment Package and deploy models using Amazon SageMaker , SageMaker Inference Pipelines , AWS Lambda , and Kubernetes . Build containerized ML services and expose them via secure, versioned RESTful APIs using FastAPI or Flask . Integrate models into real-time and batch workflows, ensuring reliability and scalability. 5. Performance Monitoring & Governance Implement robust evaluation pipelines using metrics like AUC-ROC , F1-score , Precision/Recall , Lift , and RMSE , aligned with product KPIs. Monitor model drift, data quality, and prediction stability using tools like Evidently AI , SageMaker Model Monitor , and custom telemetry. Ensure model explainability, auditability, and compliance using MLflow , SageMaker Model Registry , SHAP , and LIME . 6. MLOps & Automation Automate end-to-end ML workflows using SageMaker Pipelines , Step Functions , and CI/CD tools like GitHub Actions , CodePipeline , and Terraform . Collaborate with platform engineers to ensure reproducibility, scalability, and adherence to security and privacy standards. 7. Core ML Algorithms & Techniques Supervised Learning : Logistic Regression, Decision Trees, Random Forests, Gradient Boosting (XGBoost, LightGBM) Unsupervised Learning : K-Means, DBSCAN, PCA, t-SNE Deep Learning : CNNs, RNNs, Transformers (BERT, GPT), Autoencoders Recommendation Systems : Matrix Factorization, Neural Collaborative Filtering, Hybrid Models NLP : Text Classification, Named Entity Recognition, Embeddings, RAG Time Series Forecasting : ARIMA, Prophet, LSTM Evaluation & Tuning : Cross-validation, Hyperparameter Optimization, A/B Testing Qualifications Generative AI Applied Machine Learning & Deep Learning Software Engineering Best Practices (SOLID, Design Patterns, CI/CD) Advanced Python Development Cloud-Native ML Engineering (AWS SageMaker, Bedrock, etc.) MLOps & Model Lifecycle Management

We are looking for a highly experienced Data Scientist to lead data-driven initiatives and deliver scalable machine learning solutions to complex business problems. The ideal candidate will combine technical depth in ML/AI with strong business acumen, driving impact through advanced analytics, feature engineering, and model deployment. Key Responsibilities Partner with stakeholders to understand business objectives and translate them into data science solutions. Lead the end-to-end lifecycle of data science projects — from problem framing, data exploration, and feature engineering to model development, validation, and production deployment. Apply advanced ML algorithms (XGBoost, LightGBM, CatBoost, etc.) to solve classification, regression, and forecasting problems. Conduct clustering and unsupervised learning (KMeans, DBSCAN, hierarchical clustering) for segmentation, anomaly detection, and pattern recognition. Optimize models for accuracy, interpretability, and scalability in production environments. Build reproducible, well-documented data science workflows and collaborate closely with engineering teams on deployment. Mentor and guide junior data scientists, setting best practices in experimentation, evaluation, and MLOps. Communicate findings and recommendations to technical and non-technical stakeholders through compelling visualizations and narratives. Required Skills & Qualifications 8–12 years of professional experience in Data Science, Machine Learning, or Applied AI. Strong expertise in ML algorithms (XGBoost, LightGBM, CatBoost, ensemble methods). Solid experience in feature engineering, data preprocessing, and statistical modeling. Proficiency in clustering (KMeans, DBSCAN, etc.) and unsupervised learning techniques. Hands-on programming skills in Python (pandas, scikit-learn, NumPy, matplotlib, seaborn). Familiarity with MLOps tools, cloud platforms (AWS, Azure, GCP), and version control. Strong problem-solving skills with the ability to link analytics outcomes to business impact. Excellent communication and leadership skills with experience leading cross-functional projects.

Role Overview: We are looking for a Senior Data Scientist with a strong foundation in machine learning, data analysis, and a growing expertise in LLMs and Gen AI. The ideal candidate will be passionate about uncovering insights from data, proposing impactful use cases, and building intelligent solutions that drive business value. Key Responsibilities: Analyze structured and unstructured data to identify trends, patterns, and opportunities. Propose and validate AI/ML use cases based on business data and stakeholder needs. Build, evaluate, and deploy machine learning models for classification, regression, clustering, etc. Work with LLMs and GenAI tools to prototype and integrate intelligent solutions (e.g., chatbots, summarization, content generation). Collaborate with data engineers, product managers, and business teams to deliver end-to-end solutions. Ensure data quality, model interpretability, and ethical AI practices. Document experiments, share findings, and contribute to knowledge sharing within the team Required Skills & Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field. 3–4 years of hands-on experience in data science and machine learning. Proficient in Python and ML libraries Experience with data wrangling, feature engineering, and model evaluation. Exposure to LLMs and GenAI tools (e.g., Hugging Face, LangChain, OpenAI APIs). Familiarity with cloud platforms (AWS, GCP, or Azure) and version control (Git). Strong communication and storytelling skills with a data-driven mindset.

Job Description AuxoAI is seeking a Senior Data Scientist with deep expertise in advanced algorithms and scientific rigor to lead strategic initiatives. In this role, youll apply machine learning, causal inference, Bayesian methods, and statistical modeling to solve high-impact business problems and guide AI-native product development. This position is ideal for someone who combines technical depth with curiosity and discipline, and enjoys mentoring others while translating complexity into clarity. Location : Mumbai/Bengaluru/Hyderabad/ Gurgaon (Hybrid) Responsibilities Lead the design and development of algorithms across ML, causal inference, and AI problem spaces Conduct exploratory data analysis, feature engineering, and statistical modeling with an emphasis on interpretability and reproducibility Benchmark and optimize models using advanced algorithms such as gradient boosting (XGBoost/LightGBM), survival analysis, Bayesian hierarchical models, causal impact analysis, and probabilistic graphical models Translate complex models into clear, scalable solutions in collaboration with engineering and product teams Establish best practices for experimentation, validation frameworks, and responsible AI across projects Mentor junior data scientists and foster a high-standard, knowledge-sharing environment Stay up to date with emerging techniques in optimization, causal inference, reinforcement learning, bandits, and MCTS Requirements 6+ years of experience delivering production-grade statistical and machine learning solutions Strong foundation in hypothesis testing, Bayesian inference, and experimental design Proven experience with classical ML algorithms, including boosted trees, GLMs, survival models, and ensemble methods Proficient in Python and key libraries such as pandas/Polars, scikit-learn, and StatsModels Demonstrated ability to turn ambiguous business questions into measurable statistical models Ability to communicate insights effectively to both technical and non-technical audiences Exposure to MLOps tools and cloud-based environments is a plus Advanced degree (M./Ph.) in Statistics, Computer Science, or a related field (ref:hirist.tech)

Location: Flexible / Remote Job Type: Full-time (permanent or contract) Experience Level: Senior (6+ years engineering, 3+ years Python and data analytics, or AI) RAG pipeline, Agentic AI Job Overview We are seeking an experienced AI Engineer to design, develop, and deploy AI solutions that enhance product development workflows, engineering services, and organisational processes. The role involves applying advanced machine learning techniques to improve areas such as hardware verification, software testing, security checking, account marketing, and CRM optimisation . The ideal candidate combines strong technical expertise with the ability to translate business challenges into scalable AI solutions that are transparent, reliable, and easy to maintain. However, we would also consider applications from engineers with strong Python and data analysis skills who is keen to spend time learning the AI skills listed below. Key Responsibilities AI Model Development : Select and build appropriate AI/ML models based on problem type and business objectives. Split datasets into training/testing sets, ensuring robust evaluation and validation. Ensure models are designed for transparency, interpretability, and regular updates. Data Management & Quality : Collect, clean, and preprocess datasets from multiple sources. Ensure data relevance and accuracy while detecting and removing bias. Manage large-scale structured and unstructured datasets for modelling. Engineering Services Integration : Apply AI to improve hardware verification, software testing, and security checking . Automate processes in account marketing, CRM, and organisational workflows . Collaborate with cross-functional engineering teams to embed AI into production systems. AI Deployment & Monitoring : Deploy models into real-world environments with emphasis on scalability and reliability. Monitor performance, retrain, and refine models as needed. Maintain clear documentation and version control for reproducibility. Research & Collaboration : Stay updated with the latest trends in AI, machine learning, and automation. Work with stakeholders to identify opportunities where AI adds measurable business value. Collaborate across product, engineering, and business teams to align AI strategy with company goals. Requirements Education : Bachelor’s degree or higher in Computer Science, Engineering, Data Science, or a related field. Experience : Minimum 6+ years in engineering (software, hardware, or systems). At least 3 years in AI/ML , with hands-on experience in model development, training, and deployment. Technical Skills : Strong programming ability (Python, Java, or R). Proficiency with AI/ML frameworks (TensorFlow, PyTorch, Keras, Hugging Face). Solid knowledge of data science practices: feature engineering, training/testing pipelines, evaluation metrics. Familiarity with NLP, computer vision, and/or generative AI. Experience with cloud platforms (AWS, GCP, Azure) and DevOps (Docker, Kubernetes, CI/CD). Other Skills : Strong problem-solving, analytical, and critical thinking skills. Ability to explain complex AI concepts to non-technical stakeholders. Experience working in cross-functional and collaborative environments. Preferred Qualifications Advanced degree (Master’s or PhD) in AI, ML, Data Science, or related field. Building domain specific Co-Pilots Experience ensuring fairness, transparency, and explainability in AI systems. Background in applying AI to engineering-heavy environments (e.g., hardware verification or testing). Contributions to AI research, open-source projects, or published papers.

As a Principal/Lead AI Engineer at Simpplr, you will play a crucial role in transforming the platform from AI-enabled to AI-native. Your responsibilities will include designing, coding, and leading the development of Simpplr's AI-native platform with a focus on explainability, traceability, observability, and auditing. You will deliver enterprise-scale AI capabilities using advanced technologies such as MCP, RAG, multimodal processing, LLMs, SLMs, and custom ML models. Additionally, you will define technical strategies, align with product and engineering leaders, and champion Responsible AI principles to ensure compliance with security and governance standards. Key Responsibilities: - Design, code, and lead the build of Simpplr's AI-native platform with core capabilities of explainability, traceability, observability, and auditing. - Deliver enterprise-scale AI capabilities using technologies such as MCP, RAG, multimodal processing, LLMs, SLMs, and custom ML models. - Define technical strategy and roadmap, align with product and engineering leaders to deliver customer value at speed and scale. - Establish Responsible AI principles including bias detection, privacy-by-design, and compliance with security and governance standards. - Build robust AIOps and MLOps pipelines with versioning, CI/CD, monitoring, rollback, and drift detection. - Mentor engineers and data scientists to build high-trust and high-performance AI teams. - Partner with cross-functional teams to integrate AI into core product experiences and ensure measurable impact on user engagement and productivity. Qualifications Required: - 8+ years in applied AI/ML engineering with proven leadership in building complex, high-scale AI platforms or products. - Experience in designing and delivering advanced AI solutions using LLMs/SLMs, MCP architecture, RAG pipelines, Vector DBs, Agentic AI workflows, and automations. - Strong background in AIOps/MLOps, data engineering, and large-scale inference optimization. - Ability to build and nurture high-performing AI teams and foster a culture of innovation, accountability, and trust. - Curiosity and eagerness to learn about next generations of agentic AI workflows, personalization, and LLM-based solutions. Technical Skill Sets: - AI/ML: LLMs, MCP, RAG, multimodal generation, SLMs, prompt engineering. - Programming: Python, PyTorch/TensorFlow, scikit-learn. - Data Engineering: SQL/NoSQL, Snowflake, BigQuery, Databricks. - MLOps & AIOps: CI/CD, model versioning, monitoring, observability, Docker, Kubernetes, Kafka, Spark, MLFlow. - Cloud Infrastructure: AWS, GCP, Azure; Terraform, Ansible. - Responsible AI & Governance: Bias detection, interpretability, audit trails, privacy-by-design. You will be an ideal candidate if you are a builder-leader who can design enterprise-grade systems, ship production code, and mentor a high-performance team. Your focus on Responsible AI and operational realities will be key in creating the backbone of Simpplr's Agentic universe. Excited by the challenge of building the foundational components of an AI-native platform, you will drive innovation and excellence in AI engineering at Simpplr.,

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GDC org, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value. = 0 ? 'button' : 'presentation', 'aria-disabled': properties.TabIndex() >= 0 && viewState.displayMode() !== AppMagic.Constants.DisplayMode.Edit }, event: { click: handleClick }, shortcut: { provider: shortcutProvider, enabled: shortcutsEnabled }" data-shortcut-id="54863"> Responsibilities AI-First Delivery Leadership Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Engineering Excellence Champion high-quality engineering practices across all delivery engagements. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Promote secure coding, test-driven development, and observability as default practices. Encourage continuous learning and technical certifications to maintain cutting-edge expertise. Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions. Foster a culture of technical rigor, innovation, and accountability within the team. Innovation & Thought Leadership Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. Client Engagement & Solutioning Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Team Management & Mentorship Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence. Conduct reviews, provide feedback, and support professional development of team members. Quality & Compliance Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Strategic Partnering Serve as a strategic partner for internal and external stakeholders on key initiatives. Provide strategic guidance and execution oversight to ensure alignment with organizational goals. Other Embody our culture and values Qualifications 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight. Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture, Columnar (RedShift, Vertica) OSS (MySQL, PostgreSQL and MariaDB) CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores) Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations. Strong experience in Data Engineering: Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza) Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform. Expertise in implementation of Data governance practices using either open source or proprietary tools. Expertise in Data Ops Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Strong experience in AI/ML: Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps). Expertise in Azure ML and Open AI. Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search Good understanding of Prompt Engineering Basics. Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes. Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models. Nice To Have Skills Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling. Multi-cloud experience a plus - Azure, AWS, Google Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.