dunnhumby is the global leader in Customer Data Science, empowering businesses everywhere to compete and thrive in the modern data-driven economy. We always put the Customer First. Our mission: to enable businesses to grow and reimagine themselves by becoming advocates and champions for their Customers. With deep heritage and expertise in retail – one of the world’s most competitive markets, with a deluge of multi-dimensional data – dunnhumby today enables businesses all over the world, across industries, to be Customer First. dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Meijer, Procter & Gamble and Metro. Most companies try to meet expectations, dunnhumby exists to defy them. Using big data, deep expertise and AI-driven platforms to decode the 21st century human experience – then redefine it in meaningful and surprising ways that put customers first. Across digital, mobile and retail. For brands like Tesco, Coca-Cola, Procter & Gamble and PepsiCo. We’re looking for a Big Data Engineer to join our dh strategic team of Loyality and Personalisation which builds products the retailer can use to find the optimal customer segments and send personalised offers and digital recommendations to the consumer. These products are strategic assets to retailer to improve the loyality of their consumer. by that these products are very important for retailers and therefore for dunnhumby What We Expect From You: 3 to 6 years of experience in software development using Python. - Hands on experience in Python OOPS, Design patterns, Dependency Injection, data libraries(Panda), data structures - Exposure to Spark: PySpark, Architecture of Spark, Best practices to optimize jobs - Experience in Hadoop ecosystem: HDFS, Hive, or YARN - Experience of Orchestration tools: Airflow, Argo workflows, Kubernetes - Experience on Cloud native services(GCP/Azure/AWS) preferable GCP - Database knowledge of: SQL, NoSQL - Hands on expsoure to CI/CD pipelines for data engineering workflows - Testing: pytest for unit testing. pytest-spark to create a test Spark Session. Spark UI for Performance tuning & monitoring Good To Have: - Scala What You Can Expect From Us We won’t just meet your expectations. We’ll defy them. So you’ll enjoy the comprehensive rewards package you’d expect from a leading technology company. But also, a degree of personal flexibility you might not expect. Plus, thoughtful perks, like flexible working hours and your birthday off. You’ll also benefit from an investment in cutting-edge technology that reflects our global ambition. But with a nimble, small-business feel that gives you the freedom to play, experiment and learn. And we don’t just talk about diversity and inclusion. We live it every day – with thriving networks including dh Gender Equality Network, dh Proud, dh Family, dh One and dh Thrive as the living proof. Everyone’s invited. Our approach to Flexible Working At dunnhumby, we value and respect difference and are committed to building an inclusive culture by creating an environment where you can balance a successful career with your commitments and interests outside of work. We believe that you will do your best at work if you have a work / life balance. Some roles lend themselves to flexible options more than others, so if this is important to you please raise this with your recruiter, as we are open to discussing agile working opportunities during the hiring process. For further information about how we collect and use your personal information please see our Privacy Notice which can be found (here) What You Can Expect From Us We won’t just meet your expectations. We’ll defy them. So you’ll enjoy the comprehensive rewards package you’d expect from a leading technology company. But also, a degree of personal flexibility you might not expect. Plus, thoughtful perks, like flexible working hours and your birthday off. You’ll also benefit from an investment in cutting-edge technology that reflects our global ambition. But with a nimble, small-business feel that gives you the freedom to play, experiment and learn. And we don’t just talk about diversity and inclusion. We live it every day – with thriving networks including dh Gender Equality Network, dh Proud, dh Family, dh One, dh Enabled and dh Thrive as the living proof. We want everyone to have the opportunity to shine and perform at your best throughout our recruitment process. Please let us know how we can make this process work best for you. Our approach to Flexible Working At dunnhumby, we value and respect difference and are committed to building an inclusive culture by creating an environment where you can balance a successful career with your commitments and interests outside of work. We believe that you will do your best at work if you have a work / life balance. Some roles lend themselves to flexible options more than others, so if this is important to you please raise this with your recruiter, as we are open to discussing agile working opportunities during the hiring process. For further information about how we collect and use your personal information please see our Privacy Notice which can be found (here) Show more Show less

Job Summary We are seeking a highly experienced and customer-focused Presales Architect to join our Solution Engineering team. The ideal candidate will have a strong background in AWS IaaS, PaaS, and SaaS services , deep expertise in cloud architecture , and solid exposure to data platforms , including Amazon Redshift , AI/ML workloads , and modern data architectures . Familiarity with Azure and Google Cloud Platform (GCP) is a strong advantage. This role is a strategic blend of technical solutioning , customer engagement , and sales support , playing a critical role in the pre-sales cycle by understanding customer requirements, designing innovative solutions, and aligning them with the company’s service offerings. Key Responsibilities Pre-Sales and Solutioning: Engage with enterprise customers to understand their technical requirements and business objectives. Architect end-to-end cloud solutions on AWS , covering compute, storage, networking, DevOps, and security. Develop compelling solution proposals, high-level designs, and reference architectures that address customer needs. Support RFI/RFP responses, create technical documentation, and deliver presentations and demos to technical and non-technical audiences. Collaborate with Sales, Delivery, and Product teams to ensure alignment of proposed solutions with client expectations. Conduct technical workshops, proof of concepts (PoCs), and technical validations. Technical Expertise Deep hands-on knowledge and architecture experience with AWS services : IaaS: EC2, VPC, S3, EBS, ELB, Auto Scaling, etc. PaaS: RDS, Lambda, API Gateway, Fargate, DynamoDB, Aurora, Step Functions. SaaS & Security: AWS Organizations, IAM, AWS WAF, CloudTrail, GuardDuty. Understanding of multi-cloud strategies ; exposure to Azure and GCP cloud services including hybrid architectures is a plus. Strong knowledge of DevOps practices and tools like Terraform, CloudFormation, Jenkins, GitOps, etc. Proficiency in architecting solutions that meet scalability , availability , and security requirements. Data Platform & AI/ML Experience in designing data lakes , data pipelines , and analytics platforms on AWS. Hands-on expertise in Amazon Redshift , Athena , Glue , EMR , Kinesis , and S3-based architectures . Familiarity with AI/ML solutions using SageMaker , AWS Comprehend , or other ML frameworks. Understanding of data governance , data cataloging , and security best practices for analytics workloads. Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field. 10+ years of experience in IT, with 5+ years in cloud architecture and pre-sales roles. AWS Certified Solutions Architect – Professional (or equivalent certification) is preferred. Strong presentation skills and experience interacting with CXOs, Architects, and DevOps teams. Ability to translate technical concepts into business value propositions. Excellent communication, proposal writing, and stakeholder management skills. Nice To Have Experience with Azure (e.g., Synapse, AKS, Azure ML) or GCP (e.g., BigQuery, Vertex AI) . Familiarity with industry-specific solutions (e.g., fintech, healthcare, retail cloud transformations). Exposure to AI/ML MLOps pipelines and orchestration tools like Kubeflow , MLflow , or Airflow . Show more Show less

At Valtech, We’ve Got Opportunities To Offer You — For Growth, For Leadership, For Big, World-changing Impact And For, Dare We Say It, Fun. We Are a Global Workforce That Is Committed To Building a World That Works Better For Everyone. And That Starts With Our Kin. That’s Why We’re Proud Of The role Ideal candidates will have strong quantitative backgrounds and analytical discipline. While they will have some demonstrated ability to write code, they will not have learned programming languages for the sake of building their resume, but rather as a means to express their intellectual curiosity and analytical voice. Valtech will provide a platform and training to help them reach their full potential. Valtech is looking to hire a Business Intelligence Analyst / Data Engineer to join our growing capabilities team. If you are innovative, passionate about data and AI technologies, and look to continually learn and enjoy sharing expertise, read on! Role Responsibilities Analyze a collection of raw data sets to create meaningful impact to large enterprise clients while maintaining a high degree of scientific rigor and discipline. Engineer data pipelines and products to help stakeholders make and execute data driven decisions. Communicate analytical findings in an intuitive and visually compelling way. Creating highly visual and interactive dashboards via Tableau, PowerBI, or custom web applications Conducting deep dive analysis and designing KPIs to help guide business decisions and measure success Engineering data infrastructure, software libraries, and APIs supporting BI and ML data pipelines Architecting cloud data platform components enabling the above Building and tracking project timelines, dependences, and risks Gathering stakeholder requirements and conducting technical due diligence toward designing pragmatic data-driven business solutions Minimum Qualifications We want all new hires to succeed in their roles at Valtech. That's why we've outlined the job requirements below. To be considered for this role, it's important that you meet all Minimum Qualifications. If you do not meet all of the Preferred Qualifications, we still encourage you to apply. Proven industry experience executing data engineering, analytics, and/or data science projects or Bachelors/Masters degree in quantitative studies including Engineering, Mathematics, Statistics, Computer Science or computation-intensive Sciences and Humanities. Proficiency (can execute data ingestion to insight) in programmatic languages such as SQL, Python, and R. Preferred Qualifications Proficiency in visualization/reporting tools such as Tableau and PowerBI or programmatic visualization library such as R ggplot2, Python matplotlib/seaborn/bokeh, Javascript D3. Proficiency in big data environments and tools such as Spark, Hive, Impala, Pig, etc. Proficiency with cloud architecture components (AWS, Azure, Google) Proficiency with data pipeline software such as Airflow, Luigi, or Prefect Ability to turn raw data and ambiguous business questions into distilled findings and recommendations for action Experience with statistical and machine learning libraries along with the ability to apply them appropriately to business problems Experience leading and managing technical data/analytics/machine learning projects What We Offer You’ll join an international network of data professionals within our organisation. We support continuous development through our dedicated Academy. If you're looking to push the boundaries of innovation and creativity in a culture that values freedom and responsibility, we encourage you to apply. At Valtech, we’re here to engineer experiences that work and reach every single person. To do this, we are proactive about creating workplaces that work for every person at Valtech. Our goal is to create an equitable workplace which gives people from all backgrounds the support they need to thrive, grow and meet their goals (whatever they may be). You can find out more about what we’re doing to create a Valtech for everyone here. Please do not worry if you do not meet all of the criteria or if you have some gaps in your CV. We’d love to hear from you and see if you’re our next member of the Valtech team! Show more Show less

Job Title : Automation Engineer- Databricks Job Type : Full-time, Contractor Location : Hybrid - Hyderabad | Pune| Delhi About Us: Our mission at micro1 is to match the most talented people in the world with their dream jobs. If you are looking to be at the forefront of AI innovation and work with some of the fastest-growing companies in Silicon Valley, we invite you to apply for a role. By joining the micro1 community, your resume will become visible to top industry leaders, unlocking access to the best career opportunities on the market. Job Summary: We are seeking a detail-oriented and innovative Automation Engineer- Databricks to join our customer's team. In this critical role, you will design, develop, and execute automated tests to ensure the quality, reliability, and integrity of data within Databricks environments. If you are passionate about data quality, thrive in collaborative environments, and excel at both written and verbal communication, we'd love to meet you. Key Responsibilities: Design, develop, and maintain robust automated test scripts using Python, Selenium, and SQL to validate data integrity within Databricks environments. Execute comprehensive data validation and verification activities to ensure accuracy and consistency across multiple systems, data warehouses, and data lakes. Create detailed and effective test plans and test cases based on technical requirements and business specifications. Integrate automated tests with CI/CD pipelines to facilitate seamless and efficient testing and deployment processes. Work collaboratively with data engineers, developers, and other stakeholders to gather data requirements and achieve comprehensive test coverage. Document test cases, results, and identified defects; communicate findings clearly to the team. Conduct performance testing to ensure data processing and retrieval meet established benchmarks. Provide mentorship and guidance to junior team members, promoting best practices in test automation and data validation. Required Skills and Qualifications: Strong proficiency in Python, Selenium, and SQL for developing test automation solutions. Hands-on experience with Databricks, data warehouse, and data lake architectures. Proven expertise in automated testing of data pipelines, preferably with tools such as Apache Airflow, dbt Test, or similar. Proficient in integrating automated tests within CI/CD pipelines on cloud platforms (AWS, Azure preferred). Excellent written and verbal communication skills with the ability to translate technical concepts to diverse audiences. Bachelor’s degree in Computer Science, Information Technology, or a related discipline. Demonstrated problem-solving skills and a collaborative approach to teamwork. Preferred Qualifications: Experience with implementing security and data protection measures in data-driven applications. Ability to integrate user-facing elements with server-side logic for seamless data experiences. Demonstrated passion for continuous improvement in test automation processes, tools, and methodologies. Show more Show less

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Lead, Data Engineer Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Overview The Mastercard Services Technology team is looking for a Lead in Data Engineering, to drive our mission to unlock potential of data assets by consistently innovating, eliminating friction in how we manage big data assets, store those assets, accessibility of data and, enforce standards and principles in the Big Data space both on public cloud and on-premises set up. We are looking for a hands-on, passionate Data Engineer who is not only technically strong in PySpark, cloud platforms, and building modern data architectures, but also deeply committed to learning, growing, and lifting others. The person will play a key role in designing and building scalable data solutions, shaping our engineering culture, and mentoring team members. This is a role for builders and collaborators—engineers who love clean data pipelines, cloud-native design, and helping teammates succeed. Role Design and build scalable, cloud-native data platforms using PySpark, Python, and modern data engineering practices. Mentor and guide other engineers, sharing knowledge, reviewing code, and fostering a culture of curiosity, growth, and continuous improvement. Create robust, maintainable ETL/ELT pipelines that integrate with diverse systems and serve business-critical use cases. Lead by example—write high-quality, testable code and participate in architecture and design discussions with a long-term view in mind. Decompose complex problems into modular, efficient, and scalable components that align with platform and product goals. Champion best practices in data engineering, including testing, version control, documentation, and performance tuning. Drive collaboration across teams, working closely with product managers, data scientists, and other engineers to deliver high-impact solutions. Support data governance and quality efforts, ensuring data lineage, cataloging, and access management are built into the platform. Continuously learn and apply new technologies, frameworks, and tools to improve team productivity and platform reliability. Own and optimize cloud infrastructure components related to data engineering workflows, storage, processing, and orchestration. Participate in architectural discussions, iteration planning, and feature sizing meetings Adhere to Agile processes and participate actively in agile ceremonies Stakeholder management skills All About You 5+ years of hands-on experience in data engineering with strong PySpark and Python skills. Solid experience designing and implementing data models, pipelines, and batch/stream processing systems. Proven ability to work with cloud platforms (AWS, Azure, or GCP), especially in data-related services like S3, Glue, Data Factory, Databricks, etc. Strong foundation in data modeling, database design, and performance optimization. Understanding of modern data architectures (e.g., lakehouse, medallion) and data lifecycle management. Comfortable with CI/CD practices, version control (e.g., Git), and automated testing. Demonstrated ability to mentor and uplift junior engineers—strong communication and collaboration skills. Bachelor’s degree in computer science, Engineering, or related field—or equivalent hands-on experience. Comfortable working in Agile/Scrum development environments. Curious, adaptable, and driven by problem-solving and continuous improvement. Good To Have Experience integrating heterogeneous systems and building resilient data pipelines across cloud environments. Familiarity with orchestration tools (e.g., Airflow, dbt, Step Functions, etc.). Exposure to data governance tools and practices (e.g., Lake Formation, Purview, or Atlan). Experience with containerization and infrastructure automation (e.g., Docker, Terraform) will be a good addition. Master’s degree, relevant certifications (e.g., AWS Certified Data Analytics, Azure Data Engineer), or demonstrable contributions to open source/data engineering communities will be a bonus. Exposure to machine learning data pipelines or MLOps is a plus. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. R-251380 Show more Show less

Job Summary We are seeking a highly experienced and customer-focused Presales Architect to join our Solution Engineering team. The ideal candidate will have a strong background in AWS IaaS, PaaS, and SaaS services , deep expertise in cloud architecture , and solid exposure to data platforms , including Amazon Redshift , AI/ML workloads , and modern data architectures . Familiarity with Azure and Google Cloud Platform (GCP) is a strong advantage. This role is a strategic blend of technical solutioning , customer engagement , and sales support , playing a critical role in the pre-sales cycle by understanding customer requirements, designing innovative solutions, and aligning them with the company’s service offerings. Key Responsibilities Pre-Sales and Solutioning: Engage with enterprise customers to understand their technical requirements and business objectives. Architect end-to-end cloud solutions on AWS , covering compute, storage, networking, DevOps, and security. Develop compelling solution proposals, high-level designs, and reference architectures that address customer needs. Support RFI/RFP responses, create technical documentation, and deliver presentations and demos to technical and non-technical audiences. Collaborate with Sales, Delivery, and Product teams to ensure alignment of proposed solutions with client expectations. Conduct technical workshops, proof of concepts (PoCs), and technical validations. Technical Expertise Deep hands-on knowledge and architecture experience with AWS services : IaaS: EC2, VPC, S3, EBS, ELB, Auto Scaling, etc. PaaS: RDS, Lambda, API Gateway, Fargate, DynamoDB, Aurora, Step Functions. SaaS & Security: AWS Organizations, IAM, AWS WAF, CloudTrail, GuardDuty. Understanding of multi-cloud strategies ; exposure to Azure and GCP cloud services including hybrid architectures is a plus. Strong knowledge of DevOps practices and tools like Terraform, CloudFormation, Jenkins, GitOps, etc. Proficiency in architecting solutions that meet scalability , availability , and security requirements. Data Platform & AI/ML Experience in designing data lakes , data pipelines , and analytics platforms on AWS. Hands-on expertise in Amazon Redshift , Athena , Glue , EMR , Kinesis , and S3-based architectures . Familiarity with AI/ML solutions using SageMaker , AWS Comprehend , or other ML frameworks. Understanding of data governance , data cataloging , and security best practices for analytics workloads. Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field. 10+ years of experience in IT, with 5+ years in cloud architecture and pre-sales roles. AWS Certified Solutions Architect – Professional (or equivalent certification) is preferred. Strong presentation skills and experience interacting with CXOs, Architects, and DevOps teams. Ability to translate technical concepts into business value propositions. Excellent communication, proposal writing, and stakeholder management skills. Nice To Have Experience with Azure (e.g., Synapse, AKS, Azure ML) or GCP (e.g., BigQuery, Vertex AI) . Familiarity with industry-specific solutions (e.g., fintech, healthcare, retail cloud transformations). Exposure to AI/ML MLOps pipelines and orchestration tools like Kubeflow , MLflow , or Airflow . Show more Show less

About Beco Beco ( letsbeco.com ) is a fast-growing Mumbai-based consumer-goods company on a mission to replace everyday single-use plastics with planet-friendly, bamboo- and plant-based alternatives. From reusable kitchen towels to biodegradable garbage bags, we make sustainable living convenient, affordable and mainstream. Our founding story began with a Mumbai beach clean-up that opened our eyes to the decades-long life of a single plastic wrapper—sparking our commitment to “Be Eco” every day. Our mission: “To craft, support and drive positive change with sustainable & eco-friendly alternatives—one Beco product at a time.” Backed by marquee climate-focused VCs and now 50 + employees, we are scaling rapidly across India’s top marketplaces, retail chains and D2C channels. Why we’re hiring Sustainability at scale demands operational excellence. As volumes explode, we need data-driven, self-learning systems that eliminate manual grunt work, unlock efficiency and delight customers. You will be the first dedicated AI/ML Engineer at Beco—owning the end-to-end automation roadmap across Finance, Marketing, Operations, Supply Chain and Sales. Responsibilities Partner with functional leaders to translate business pain-points into AI/ML solutions and automation opportunities. Own the complete lifecycle: data discovery, cleaning, feature engineering, model selection, training, evaluation, deployment and monitoring. Build robust data pipelines (SQL/BigQuery, Spark) and APIs to integrate models with ERP, CRM and marketing automation stacks. Stand up CI/CD + MLOps (Docker, Kubernetes, Airflow, MLflow, Vertex AI/SageMaker) for repeatable training and one-click releases. Establish data-quality, drift-detection and responsible-AI practices (bias, transparency, privacy). Mentor analysts & engineers; evangelise a culture of experimentation and “fail-fast” learning—core to Beco’s GSD (“Get Sh#!t Done”) values. Must-have Qualifications 3 + years hands-on experience delivering ML, data-science or intelligent-automation projects in production. Proficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow) and SQL; solid grasp of statistics, experimentation and feature engineering. Experience building and scaling ETL/data pipelines on cloud (GCP, AWS or Azure). Familiarity with modern Gen-AI & NLP stacks (OpenAI, Hugging Face, RAG, vector databases). Track record of collaborating with cross-functional stakeholders and shipping iteratively in an agile environment. Nice-to-haves Exposure to e-commerce or FMCG supply-chain data. Knowledge of finance workflows (Reconciliation, AR/AP, FP&A) or RevOps tooling (HubSpot, Salesforce). Experience with vision models (Detectron2, YOLO) and edge deployment. Contributions to open-source ML projects or published papers/blogs. What Success Looks Like After 1 Year 70 % reduction in manual reporting hours across finance and ops. Forecast accuracy > 85 % at SKU level, slashing stock-outs by 30 %. AI chatbot resolves 60 % of tickets end-to-end, with CSAT > 4.7/5. At least two new data-products launched that directly boost topline or margin. Life at Beco Purpose-driven team obsessed with measurable climate impact. Entrepreneurial, accountable, bold” culture—where winning minds precede outside victories. Show more Show less

Maximize Your Impact with TP Welcome to TP, a global hub of innovation and empowerment, where we redefine the future. With a remarkable €10 billion annual revenue and a global team of 500,000 employees serving 170 countries in over 300 languages, we lead in intelligent, digital-first solutions. As a globally certified Great Place to Work in 72 countries, our culture thrives on diversity, equity, and inclusion. We value your unique perspective and believe that your talent is the missing piece that completes our vision for a brighter, digitally driven tomorrow. The Opportunity The AI Data Engineer designs, develops, and maintains robust data pipelines to support AI data services operations, ensuring smooth ingestion, transformation, and extraction of large, multilingual, and multimodal datasets. This role collaborates with cross-functional teams to optimize data workflows, implement quality checks, and deliver scalable solutions that underpin our analytics and AI/ML initiatives. The Responsibilities Create and manage ETL workflows using Python and relevant libraries (e.g., Pandas, NumPy) for high-volume data processing. Monitor and optimize data workflows to reduce latency, maximize throughput, and ensure high-quality data availability. Work with Platform Operations, QA, and Analytics teams to guarantee seamless data integration and consistent data accuracy. Implement validation processes and address anomalies or performance bottlenecks in real time. Develop REST API integrations and Python scripts to automate data exchanges with internal systems and BI dashboards. Maintain comprehensive technical documentation, data flow diagrams, and best-practice guidelines. The Qualifications Bachelor’s degree in Computer Science, Data Engineering, Information Technology, or a related field. Relevant coursework in Python programming, database management, or data integration techniques. 3–5 years of professional experience in data engineering, ETL development, or similar roles. Proven track record of building and maintaining scalable data pipelines. Experience working with SQL databases (e.g., MySQL, PostgreSQL) and NoSQL solutions (e.g., MongoDB). AWS Certified Data Analytics – Specialty, Google Cloud Professional Data Engineer, or similar certifications are a plus. Advanced Python proficiency with data libraries (Pandas, NumPy, etc.). Familiarity with ETL/orchestration tools (e.g., Apache Airflow). Understanding of REST APIs and integration frameworks. Experience with version control (Git) and continuous integration practices. Exposure to cloud-based data solutions (AWS, Azure, or GCP) is advantageous. Pre-Employment Screenings By TP policy, employment in this position will be contingent on your successful completion and passage of a comprehensive background check, including global sanctions and watch list screening. Important | Policy on Unsolicited Third-Party Candidate Submissions TP does not accept candidate submissions from unsolicited third parties, including recruiters or headhunters. Applications will not be considered, and no contractual association will be established through such submissions. Diversity, Equity & Inclusion At TP, we are committed to fostering a diverse, equitable, and inclusive workplace. We welcome individuals from all backgrounds and lifestyles and do not discriminate based on gender identity or expression, sexual orientation, race, religion, age, national origin, citizenship, disability, pregnancy status, veteran status, or other differences. Show more Show less

We are hiring for immediate joiners. This is a Remote mode job. Job Title: GCP Data Engineer (Google Cloud Platform) Experience : 4 + Years Location: Chennai (Hybrid) Responsibilities Google Cloud Platform - Biq Query, Data Flow, Dataproc, Data Fusion, TERRAFORM, Tekton,Cloud SQL, AIRFLOW, POSTGRES, Airflow PySpark, Python, API 2+Years in GCP Services - Biq Query, Data Flow, Dataproc, DataPlex,DataFusion, Terraform, Tekton, Cloud SQL, Redis Memory, Airflow, Cloud Storage 2+ Years in Data Transfer Utilities 2+ Years in Git / any other version control tool 2+ Years in Confluent Kafka 1+ Years of Experience in API Development 2+ Years in Agile Framework 4+ years of strong experience in python, Pyspark development. 4+ years of shell scripting to develop the adhoc jobsfor data importing/exporting. Show more Show less

Job Title : GenAI / ML Engineer Function : Research & Development Location : Delhi/Bangalore (3 days in office) About the Company: Elucidata is a TechBio Company headquartered in San Francisco. Our mission is to make life sciences data AI-ready. Elucidata's Elucidata’s LLM-powered platform Polly, helps research teams wrangle, store, manage and analyze large volumes of biomedical data. We are at the forefront of driving GenAI in life sciences R&D across leading BioPharma companies like Pfizer, Janssen, NextGen Jane and many more. We were recognised as the 'Most Innovative Biotech Company, 2024', by Fast Company. We are a 120+ multi-disciplinary team of experts based across the US and India. In September 2022, we raised $16 million in our Series A round led by Eight Roads, F-Prime, and our existing investors Hyperplane and IvyCap. About the Role: We are looking for a GenAI / ML Engineer to join our R&D team and work on cutting-edge applications of LLMs in biomedical data processing . In this role, you'll help build and scale intelligent systems that can extract, summarize, and reason over biomedical knowledge from large bodies of unstructured text, including scientific publications, EHR/EMR reports, and more. You’ll work closely with data scientists, biomedical domain experts, and product managers to design and implement reliable GenAI-powered workflows — from rapid prototypes to production-ready solutions. This is a highly strategic role as we continue to invest in agentic AI systems and LLM-native infrastructure to power the next generation of biomedical applications. Key Responsibilities: Build and maintain LLM-powered pipelines for entity extraction, ontology normalization, Q&A, and knowledge graph creation using tools like LangChain, LangGraph, and CrewAI. Fine-tune and deploy open-source LLMs (e.g., LLaMA, Gemma, DeepSeek, Mistral) for biomedical applications. Define evaluation frameworks to assess accuracy, efficiency, hallucinations, and long-term performance; integrate human-in-the-loop feedback. Collaborate cross-functionally with data scientists, bioinformaticians, product teams, and curators to build impactful AI solutions. Stay current with the LLM ecosystem and drive adoption of cutting-edge tools, models, and methods. Qualifications : 2–3 years of experience as an ML engineer, data scientist, or data engineer working on NLP or information extraction. Strong Python programming skills and experience building production-ready codebases. Hands-on experience with LLM frameworks and tooling (e.g., LangChain, HuggingFace, OpenAI APIs, Transformers). Familiarity with one or more LLM families (e.g., LLaMA, Mistral, DeepSeek, Gemma) and prompt engineering best practices. Strong grasp of ML/DL fundamentals and experience with tools like PyTorch, or TensorFlow. Ability to communicate ideas clearly, iterate quickly, and thrive in a fast-paced, product-driven environment. Good to Have (Preferred but Not Mandatory) Experience working with biomedical or clinical text (e.g., PubMed, EHRs, trial data). Exposure to building autonomous agents using CrewAI or LangGraph. Understanding of knowledge graph construction and integration with LLMs. Experience with evaluation challenges unique to GenAI workflows (e.g., hallucination detection, grounding, traceability). Experience with fine-tuning, LoRA, PEFT, or using embeddings and vector stores for retrieval. Working knowledge of cloud platforms (AWS/GCP) and MLOps tools (MLflow, Airflow etc.). Contributions to open-source LLM or NLP tooling We are proud to be an equal-opportunity workplace and are an affirmative action employer. We are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Show more Show less

Job Description Our company is an innovative, global healthcare leader that is committed to improving health and well-being around the world with a diversified portfolio of prescription medicines, vaccines and animal health products. We continue to focus our research on conditions that affect millions of people around the world - diseases like Alzheimer's, diabetes and cancer - while expanding our strengths in areas like vaccines and biologics. Our ability to excel depends on the integrity, knowledge, imagination, skill, diversity and teamwork of an individual like you. To this end, we strive to create an environment of mutual respect, encouragement and teamwork. As part of our global team, you’ll have the opportunity to collaborate with talented and dedicated colleagues while developing and expanding your career. As a Digital Supply Chain Data Modeler/Engineer, you will work as a member of the Digital Manufacturing Division team supporting Enterprise Orchestration Platform. You will be responsible for identifying, assessing, and solving complex business problems related to manufacturing and supply chain. You will receive training to achieve this, and you’ll be amazed at the diversity of opportunities to develop your potential and grow professionally. You will collaborate with business stakeholders and determine analytical capabilities that will enable the creation of Insights-focused solutions that align to business needs and ensure that delivery of these solutions meet quality requirements. The Opportunity Based in Hyderabad, joining a global healthcare biopharma company and be part of a 130- year legacy of success backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare. Be part of an organization driven by digital technology and data-backed approaches that support a diversified portfolio of prescription medicines, vaccines, and animal health products. Drive innovation and execution excellence. Be a part of a team with passion for using data, analytics, and insights to drive decision-making, and which creates custom software, allowing us to tackle some of the world's greatest health threats. Our Technology Centers focus on creating a space where teams can come together to deliver business solutions that save and improve lives. An integral part of our company’s IT operating model, Tech Centers are globally distributed locations where each IT division has employees to enable our digital transformation journey and drive business outcomes. These locations, in addition to the other sites, are essential to supporting our business and strategy. A focused group of leaders in each Tech Centre helps to ensure we can manage and improve each location, from investing in growth, success, and well-being of our people, to making sure colleagues from each IT division feel a sense of belonging to managing critical emergencies. And together, we must leverage the strength of our team to collaborate globally to optimize connections and share best practices across the Tech Centers. Job Description As Data modeler lead, you will be responsible for following Deliver divisional analytics initiatives with primary focus on datamodeling for all analytics, advanced analytics and AI/ML uses cases e,g Self Services , Business Intelligence & Analytics, Data exploration, Data Wrangling etc. Host and lead requirement/process workshop to understand the requirements of datamodeling . Analysis of business requirements and work with architecture team to deliver & contribute to feasibility analysis, implementation plans and high-level estimates. Based on business process and analysis of data sources, deliver detailed ETL design with mapping of data model covering all areas of Data warehousing for all analytics use cases . Creation of data model & transformation mapping in modeling tool and deploy in databases including creation of schedule orchestration jobs . Deployment of Data modeling configuration to Target systems (SIT , UAT & Prod ) . Understanding of Product owership and management. Lead Data model as a product for focus areas of Digital supply chain domain. Creation of required SDLC documentation as per project requirements. Optimization/industrialization of existing database and data transformation solution Prepare and update Data modeling and Data warehousing best practices along with foundational platforms. Work very closely with foundational product teams, Business, vendors and technology support teams to build team to deliver business initiatives . Position Qualifications : Education Minimum Requirement: - B.S. or M.S. in IT, Engineering, Computer Science, or related field. Required Experience and Skills**: 5+ years of relevant work experience, with demonstrated expertise in Data modeling in DWH, Data Mesh or any analytics related implementation; experience in implementing end to end DWH solutions involving creating design of DWH and deploying the solution 3+ years of experience in creating logical & Physical data model in any modeling tool ( SAP Power designer, WhereScape etc ). Experience in creating data modeling standards, best practices and Implementation process. High Proficiency in Information Management, Data Analysis and Reporting Requirement Elicitation Experience working with extracting business rules to develop transformations, data lineage, and dimension data modeling Experience working with validating legacy and developed data model outputs Development experience using WhereScape and various similar ETL/Data Modeling tools Exposure to Qlik or similar BI dashboarding applications Has advanced knowledge of SQL and data transformation practices Has deep understanding of data modelling and preparation of optimal data structures Is able to communicate with business, data transformation team and reporting team Has knowledge of ETL methods, and a willingness to learn ETL technologies Can fluently communicate in English Experience in Redshift or similar databases using DDL, DML, Query optimization, Schema management, Security, etc Experience with Airflow or similar various orchestration tools Exposure to CI/CD tools Exposure to AWS modules such as S3, AWS Console, Glue, Spectrum, etc management Independently support business discussions, analyze, and develop/deliver code Preferred Experience and Skills: Experience working on projects where Agile methodology is leveraged Understanding of data management best practices and data analytics Ability to lead requirements sessions with clients and project teams Strong leadership, verbal and written communication skills with ability to articulate results and issues to internal and client teams Demonstrated experience in the Life Science space Exposure to SAP and Rapid Response domain data is a plus Current Employees apply HERE Current Contingent Workers apply HERE Search Firm Representatives Please Read Carefully Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails. Employee Status: Regular Relocation: VISA Sponsorship: Travel Requirements: Flexible Work Arrangements: Hybrid Shift: Valid Driving License: Hazardous Material(s): Required Skills: Agile Data Warehousing, Agile Methodology, Animal Vaccination, Business, Business Communications, Business Initiatives, Business Intelligence (BI), Computer Science, Database Administration, Data Engineering, Data Management, Data Modeling, Data Visualization, Data Warehousing (DW), Design Applications, Digital Supply Chain, Digital Supply Chain Management, Digital Transformation, Information Management, Information Technology Operations, Software Development, Software Development Life Cycle (SDLC), Supply Chain Optimization, Supply Management, System Designs Preferred Skills: Job Posting End Date: 07/31/2025 A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date. Requisition ID: R352794

MongoDB’s mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unleash AI. Our industry-leading developer data platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available in more than 115 regions across AWS, Google Cloud, and Microsoft Azure. Atlas allows customers to build and run applications anywhere—on premises, or across cloud providers. With offices worldwide and over 175,000 new developers signing up to use MongoDB every month, it’s no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications. Summary As an Analytics Engineer at MongoDB, you will play a critical role in leveraging data to drive informed decision-making and simplify end user engagement across our most critical data sets. You will be responsible for designing, developing, and maintaining robust analytics solutions, ensuring data integrity, and enabling data-driven insights across all of MongoDB. This role requires an analytical thinker with strong technical expertise to contribute to the growth and success of the entire business. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. Responsibilities Design, implement, and maintain highly performant data post-processing pipelines Create shared data assets that will act as the company’s source-of-truth for critical business metrics Partner with analytics stakeholders to curate analysis-ready datasets and augment the generation of actionable insights Partner with data engineering to expose governed datasets to the rest of the organization Make impactful contributions to our analytics infrastructure, systems, and tools Create and manage documentation, and conduct knowledge sharing sessions to proliferate tribal knowledge and best practices Maintain consistent planning and tracking of work in JIRA tickets Skills & Attributes Bachelor’s degree (or equivalent) in mathematics, computer science, information technology, engineering, or related discipline 2-4 years of relevant experience Strong Proficiency in SQL and experience working with relational databases Solid understanding of data modeling and ETL processes Proficiency in Python for data manipulation and analysis Familiarity with CI/CD concepts and experience with managing codebases with git Experience managing ETL and data pipeline orchestration with dbt and Airflow Familiarity with basic command line functions Experience translating project requirements into a set of technical sub-tasks that build towards a final deliverable Committed to continuous improvement, with a passion for building processes/tools to make everyone more efficient The ability to effectively collaborate cross-functionally to drive actionable and measurable results A passion for AI as an enhancing tool to improve workflows, increase productivity, and generate smarter outcomes Strong communication skills to document technical processes clearly and lead knowledge-sharing efforts across teams A desire to constantly learn and improve themselves To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world! MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter. MongoDB is an equal opportunities employer. Req ID - 2263168254 Show more Show less

JOB DESCRIPTION Key Responsibilities:  Prior experience in migrating from IBM DataStage to DBT and BigQuery or similar data migration activities into the cloud solutions.  Design and implement modular, testable, and scalable DBT models aligned with business logic and performance needs.  Optimize and manage BigQuery datasets, partitioning, clustering, and cost-efficient querying.  Collaborate with stakeholders to understand existing pipelines and translate them into modern ELT workflows.  Establish best practices for version control, CI/CD, testing, and documentation in DBT.  Provide technical leadership and mentorship to team members during the migration process.  Ensure high standards of data quality, governance, and security. Required Qualifications:  6+ years of experience in data engineering, with at least 3+ years hands-on with DBT and BigQuery.  Strong understanding of SQL, data warehousing, and ELT architecture.  Experience with data modeling (especially dimensional modeling) and performance tuning in BigQuery.  Familiarity with legacy ETL tools like IBM DataStage and ability to reverse-engineer existing pipelines.  Proficiency in Git, CI/CD pipelines, and dataOps practices.  Excellent communication skills and ability to work independently and collaboratively. Preferred Qualifications:  Experience in cloud migration projects (especially GCP).  Knowledge of data governance, access control, and cost optimization in BigQuery.  Exposure to orchestration tools like Airflow.  Familiarity with Agile methodologies and cross-functional team collaboration. Show more Show less

About Us: G3 Interactive is a Kochi-based software development company now expanding into AI, data engineering, and advanced analytics due to growing customer demand. We’re seeking a Data Engineer / Data Scientist with a strong foundation in data processing and analytics — and experience with Databricks is a significant advantage. What You’ll Do: Build and manage scalable data pipelines and ELT workflows using modern tools. Design and implement predictive models using Python (pandas, scikit-learn) . Leverage platforms like Databricks for distributed processing and ML workflows. Collaborate with internal and client teams to deliver data-driven solutions . Create insightful dashboards using Metabase or other BI tools. Maintain high-quality standards in data management and governance. Must-Have Skills: 2–3 years’ experience in Data Science, Data Engineering, or a similar role. Strong Python skills with expertise in pandas and data structures. Experience writing efficient SQL queries. Understanding of ML models, statistical analysis, and data wrangling. Excellent communication and collaboration skills. Bonus / Advantage: Experience with Databricks (ETL, notebooks, ML pipelines, Delta Lake, etc.). Familiarity with Spark, Airflow, AWS, or Google Cloud. Knowledge of CI/CD for data workflows. Job Types: Full-time, Permanent Pay: ₹25,000.00 - ₹35,000.00 per month Schedule: Day shift Education: Master's (Preferred) Experience: data engineering: 2 years (Preferred) Work Location: In person

You Lead the Way. We’ve Got Your Back. At American Express, we know that with the right backing, people and businesses have the power to progress in incredible ways. Whether we’re supporting our customers’ financial confidence to move ahead, taking commerce to new heights, or encouraging people to explore the world, our colleagues are constantly redefining what’s possible — and we’re proud to back each other every step of the way. When you join #TeamAmex, you become part of a diverse community of over 60,000 colleagues, all with a common goal to deliver an exceptional customer experience every day. We back our colleagues with the support they need to thrive, professionally and personally. That’s why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. We are building an energetic, high-performance team with a nimble and creative mindset to drive our technology and products. American Express (AXP) is a powerful brand, a great place to work and has unparalleled scale. Join us for an exciting opportunity in the Marketing Technology within American Express Technologies. How will you make an impact in this role? There are hundreds of opportunities to make your mark on technology and life at American Express. Here's just some of what you'll be doing: As a part of our team, you will be developing innovative, high quality, and robust operational engineering capabilities. Develop software in our technology stack which is constantly evolving but currently includes Big data, Spark, Python, Scala, GCP, Adobe Suit ( like Customer Journey Analytics ). Work with Business partners and stakeholders to understand functional requirements, architecture dependencies, and business capability roadmaps. Create technical solution designs to meet business requirements. Define best practices to be followed by team. Taking your place as a core member of an Agile team driving the latest development practices Identify and drive reengineering opportunities, and opportunities for adopting new technologies and methods. Suggest and recommend solution architecture to resolve business problems. Perform peer code review and participate in technical discussions with the team on the best solutions possible. As part of our diverse tech team, you can architect, code and ship software that makes us an essential part of our customers' digital lives. Here, you can work alongside talented engineers in an open, supportive, inclusive environment where your voice is valued, and you make your own decisions on what tech to use to solve challenging problems. American Express offers a range of opportunities to work with the latest technologies and encourages you to back the broader engineering community through open source. And because we understand the importance of keeping your skills fresh and relevant, we give you dedicated time to invest in your professional development. Find your place in technology of #TeamAmex. Minimum Qualifications: BS or MS degree in computer science, computer engineering, or other technical discipline, or equivalent work experience. 5+ years of hands-on software development experience with Big Data & Analytics solutions – Hadoop Hive, Spark, Scala, Hive, Python, shell scripting, GCP Cloud Big query, Big Table, Airflow. Working knowledge of Adobe suit like Adobe Experience Platform, Adobe Customer Journey Analytics, CDP. Proficiency in SQL and database systems, with experience in designing and optimizing data models for performance and scalability. Design and development experience with Kafka, Real time ETL pipeline, API is desirable. Experience in designing, developing, and optimizing data pipelines for large-scale data processing, transformation, and analysis using Big Data and GCP technologies. Certifications in cloud platform (GCP Professional Data Engineer) is a plus. Understanding of distributed (multi-tiered) systems, data structures, algorithms & Design Patterns. Strong Object-Oriented Programming skills and design patterns. Experience with CICD pipelines, Automated test frameworks, and source code management tools (XLR, Jenkins, Git, Maven). Good knowledge and experience with configuration management tools like GitHub Ability to analyze complex data engineering problems, propose effective solutions, and implement them effectively. Looks proactively beyond the obvious for continuous improvement opportunities. Communicates effectively with product and cross functional team. We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place. Your Impact As a Data Engineer I at McKinsey & Company, you will play a key role in designing, building, and deploying scalable data pipelines and infrastructure that enable our analytics and AI solutions. You will work closely with product managers, developers, asset owners, and client stakeholders to turn raw data into trusted, structured, and high-quality datasets used in decision-making and advanced analytics. Your core responsibilities will include: Developing robust, scalable data pipelines for ingesting, transforming, and storing data from multiple structured and unstructured sources using Python/SQL. Creating and optimizing data models and data warehouses to support reporting, analytics, and application integration. Working with cloud-based data platforms (AWS, Azure, or GCP) to build modern, efficient, and secure data solutions. Contributing to R&D projects and internal asset development. Contributing to infrastructure automation and deployment pipelines using containerization and CI/CD tools. Collaborating across disciplines to integrate data engineering best practices into broader analytical and generative AI (gen AI) workflows. Supporting and maintaining data assets deployed in client environments with a focus on reliability, scalability, and performance. Furthermore, you will have opportunity to explore and contribute to solutions involving generative AI, such as vector embeddings, retrieval-augmented generation (RAG), semantic search, and LLM-based prompting, especially as we integrate gen AI capabilities into our broader data ecosystem. Your Growth Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward. In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else. When you join us, you will have: Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey. A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes. Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences. World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package, which includes medical, dental, mental health, and vision coverage for you, your spouse/partner, and children. Your qualifications and skills Bachelor’s degree in computer science, engineering, mathematics, or a related technical field (or equivalent practical experience). 3+ years of experience in data engineering, analytics engineering, or a related technical role. Strong Python programming skills with demonstrated experience building scalable data workflows and ETL/ELT pipelines. Proficient in SQL with experience designing normalized and denormalized data models. Hands-on experience with orchestration tools such as Airflow, Kedro, or Azure Data Factory (ADF). Familiarity with cloud platforms (AWS, Azure, or GCP) for building and managing data infrastructure. Discernable communication skills, especially around breaking down complex structures into digestible and relevant points for a diverse set of clients and colleagues, at all levels. High-value personal qualities including critical thinking and creative problem-solving skills; an ability to influence and work in teams. Entrepreneurial mindset and ownership mentality are must; desire to learn and develop, within a dynamic, self-led organization. Hands-on experience with containerization technologies (Docker, Docker-compose). Hands on experience with automation frameworks (Github Actions, CircleCI, Jenkins, etc.). Exposure to generative AI tools or concepts (e.g., OpenAI, Cohere, embeddings, vector databases). Experience working in Agile teams and contributing to design and architecture discussions. Contributions to open-source projects or active participation in data engineering communities.

HR Contact No. 6395012950 Job Title: Design Engineer – HVAC Manufacturing Location: Gujarat Department: Engineering/Design Reports To: MD Job Type: Full-Time Position Overview: We are seeking a talented and detail-oriented Design Engineer to join our engineering team in a dynamic HVAC manufacturing environment. The ideal candidate will have a strong background in mechanical design, proficiency in AutoCAD , and hands-on experience with nesting software for sheet metal fabrication. This role is critical to the development and production of high-quality HVAC components and systems, supporting product design, customization, and manufacturing optimization. Key Responsibilities: Design HVAC components and assemblies using AutoCAD/Nesting based on project specifications. Create and manage detailed 2D and 3D drawings, BOMs, and technical documentation. Prepare nesting layouts using nesting software for sheet metal cutting operations. Collaborate with production and fabrication teams to ensure manufacturability and cost-efficiency of designs. Modify and improve existing designs to meet performance and production requirements. Work with the Customers and Sales team to develop a quotable/manufacturing solution to the customer request. Ensure timely output drawings for customer approval Participate in new product development and R&D initiatives. Visiting Project sites as per requirement. Ensure all designs comply with industry standards and company quality procedures. Assist in resolving manufacturing and assembly issues related to design. Required Qualifications: Diploma or Bachelor's Degree in Mechanical Engineering, Manufacturing Engineering, or related field. Minimum of 2–5 years of experience in a design engineering role within a manufacturing environment, preferably HVAC. Proficiency in AutoCAD (2D required, 3D is a plus). Hands-on experience with nesting software (e.g., SigmaNEST, NestFab, or similar). Solid understanding of sheet metal fabrication processes and design principles. Strong analytical, problem-solving, and communication skills. Ability to interpret technical drawings and specifications. Experience working in a cross-functional team environment. Preferred Qualifications: Familiarity with HVAC system components and airflow principles. Experience with additional CAD/CAM software (e.g., SolidWorks, Inventor). Knowledge of lean manufacturing or value engineering practices. Job Type: Full-time Pay: ₹15,000.00 - ₹20,000.00 per month Benefits: Paid time off Provident Fund Schedule: Day shift Supplemental Pay: Yearly bonus Work Location: In person

We are accepting applications for experienced Data Engineer with a strong background in data scraping, cleaning, transformation, and automation. The ideal candidate will be responsible for building robust data pipelines, maintaining data integrity, and generating actionable dashboards and reports to support business decision-making. Key Responsibilities: Develop and maintain scripts for scraping data from various sources including APIs, websites, and databases. Perform data cleaning, transformation, and normalization to ensure consistency and usability across all data sets. Design and implement relational and non-relational data tables and frames for scalable data storage and analysis. Build automated data pipelines to ensure timely and accurate data availability. Create and manage interactive dashboards and reports using tools such as Power BI, Tableau, or similar platforms. Write and maintain data automation scripts to streamline ETL (Extract, Transform, Load) processes. Ensure data quality, governance, and compliance with internal and external regulations. Monitor and optimize the performance of data workflows and pipelines. Qualifications & Skills: Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field. Minimum of 5 years of experience in a data engineering or similar role. Proficient in Python (especially for data scraping and automation), and strong hands-on experience with Pandas, NumPy , and other data manipulation libraries. Experience with web scraping tools and techniques (e.g., BeautifulSoup, Scrapy, Selenium). Strong SQL skills and experience working with relational databases (e.g., PostgreSQL, MySQL) and data warehouses (e.g., Redshift, Snowflake, BigQuery). Familiarity with data visualization tools like Power BI, Tableau, or Looker. Knowledge of ETL tools and orchestration frameworks such as Apache Airflow, Luigi, or Prefect . Experience with version control systems like Git and collaborative platforms like Jira or Confluence . Strong understanding of data security, privacy , and governance best practices. Excellent problem-solving skills and attention to detail. Preferred Qualifications: Experience with cloud platforms such as AWS, GCP, or Azure. Familiarity with NoSQL databases like MongoDB, Cassandra, or Elasticsearch. Understanding of CI/CD pipelines and DevOps practices related to data engineering. Job Type: Full-Time (In-Office) Work Days: Monday to Saturday Job Types: Full-time, Permanent Pay: ₹700,000.00 - ₹1,500,000.00 per year Schedule: Day shift Work Location: In person

About The Role We are seeking a highly skilled Data Engineer with deep expertise in PySpark and the Cloudera Data Platform (CDP) to join our data engineering team. As a Data Engineer, you will be responsible for designing, developing, and maintaining scalable data pipelines that ensure high data quality and availability across the organization. This role requires a strong background in big data ecosystems, cloud-native tools, and advanced data processing techniques. The ideal candidate has hands-on experience with data ingestion, transformation, and optimization on the Cloudera Data Platform, along with a proven track record of implementing data engineering best practices. You will work closely with other data engineers to build solutions that drive impactful business insights. Responsibilities Data Pipeline Development: Design, develop, and maintain highly scalable and optimized ETL pipelines using PySpark on the Cloudera Data Platform, ensuring data integrity and accuracy. Data Ingestion: Implement and manage data ingestion processes from a variety of sources (e.g., relational databases, APIs, file systems) to the data lake or data warehouse on CDP. Data Transformation and Processing: Use PySpark to process, cleanse, and transform large datasets into meaningful formats that support analytical needs and business requirements. Performance Optimization: Conduct performance tuning of PySpark code and Cloudera components, optimizing resource utilization and reducing runtime of ETL processes. Data Quality and Validation: Implement data quality checks, monitoring, and validation routines to ensure data accuracy and reliability throughout the pipeline. Automation and Orchestration: Automate data workflows using tools like Apache Oozie, Airflow, or similar orchestration tools within the Cloudera ecosystem. Education and Experience Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, or a related field. 3+ years of experience as a Data Engineer, with a strong focus on PySpark and the Cloudera Data Platform. Technical Skills PySpark: Advanced proficiency in PySpark, including working with RDDs, DataFrames, and optimization techniques. Cloudera Data Platform: Strong experience with Cloudera Data Platform (CDP) components, including Cloudera Manager, Hive, Impala, HDFS, and HBase. Data Warehousing: Knowledge of data warehousing concepts, ETL best practices, and experience with SQL-based tools (e.g., Hive, Impala). Big Data Technologies: Familiarity with Hadoop, Kafka, and other distributed computing tools. Orchestration and Scheduling: Experience with Apache Oozie, Airflow, or similar orchestration frameworks. Scripting and Automation: Strong scripting skills in Linux. Show more Show less

Role: Data Engineer Key Skill: Pyspark, Cloudera Data Platfrorm, Big data - Hadoop, Hive, Kafka Responsibilities Data Pipeline Development: Design, develop, and maintain highly scalable and optimized ETL pipelines using PySpark on the Cloudera Data Platform, ensuring data integrity and accuracy. Data Ingestion: Implement and manage data ingestion processes from a variety of sources (e.g., relational databases, APIs, file systems) to the data lake or data warehouse on CDP. Data Transformation and Processing: Use PySpark to process, cleanse, and transform large datasets into meaningful formats that support analytical needs and business requirements. Performance Optimization: Conduct performance tuning of PySpark code and Cloudera components, optimizing resource utilization and reducing runtime of ETL processes. Data Quality and Validation: Implement data quality checks, monitoring, and validation routines to ensure data accuracy and reliability throughout the pipeline. Automation and Orchestration: Automate data workflows using tools like Apache Oozie, Airflow, or similar orchestration tools within the Cloudera ecosystem. Technical Skills 3+ years of experience as a Data Engineer, with a strong focus on PySpark and the Cloudera Data Platform PySpark: Advanced proficiency in PySpark, including working with RDDs, DataFrames, and optimization techniques. Cloudera Data Platform: Strong experience with Cloudera Data Platform (CDP) components, including Cloudera Manager, Hive, Impala, HDFS, and HBase. Data Warehousing: Knowledge of data warehousing concepts, ETL best practices, and experience with SQL-based tools (e.g., Hive, Impala). Big Data Technologies: Familiarity with Hadoop, Kafka, and other distributed computing tools. Orchestration and Scheduling: Experience with Apache Oozie, Airflow, or similar orchestration frameworks. Scripting and Automation: Strong scripting skills in Linux. Show more Show less

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate Job Description & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions. *Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us . At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. " Job Description & Summary: A career within…. A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. Responsibilities: Design, develop, and optimize data pipelines and ETL processes using PySpark or Scala to extract, transform, and load large volumes of structured and unstructured data from diverse sources. Implement data ingestion, processing, and storage solutions on Azure cloud platform, leveraging services such as Azure Databricks, Azure Data Lake Storage, and Azure Synapse Analytics. Develop and maintain data models, schemas, and metadata to support efficient data access, query performance, and analytics requirements. Monitor pipeline performance, troubleshoot issues, and optimize data processing workflows for scalability, reliability, and cost-effectiveness. Implement data security and compliance measures to protect sensitive information and ensure regulatory compliance. Requirement Proven experience as a Data Engineer, with expertise in building and optimizing data pipelines using PySpark, Scala, and Apache Spark. Hands-on experience with cloud platforms, particularly Azure, and proficiency in Azure services such as Azure Databricks, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL Database. Strong programming skills in Python and Scala, with experience in software development, version control, and CI/CD practices. Familiarity with data warehousing concepts, dimensional modeling, and relational databases (e.g., SQL Server, PostgreSQL, MySQL). Experience with big data technologies and frameworks (e.g., Hadoop, Hive, HBase) is a plus. Mandatory skill sets: Spark, Pyspark, Azure Preferred skill sets: Spark, Pyspark, Azure Years of experience required: 4 - 8 Education qualification: B.Tech / M.Tech / MBA / MCA Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Bachelor of Technology, Master of Business Administration Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Microsoft Azure Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 27 more} Desired Languages (If blank, desired languages not specified) Travel Requirements Not Specified Available for Work Visa Sponsorship? No Government Clearance Required? No Job Posting End Date

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager Job Description & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions. *Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us . At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. Job Description & Summary: A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. Responsibilities : Design, develop, and optimize data pipelines and ETL processes using PySpark or Scala to extract, transform, and load large volumes of structured and unstructured data from diverse sources. Implement data ingestion, processing, and storage solutions on Azure cloud platform, leveraging services such as Azure Databricks, Azure Data Lake Storage, and Azure Synapse Analytics. Develop and maintain data models, schemas, and metadata to support efficient data access, query performance, and analytics requirements. Monitor pipeline performance, troubleshoot issues, and optimize data processing workflows for scalability, reliability, and cost-effectiveness. Implement data security and compliance measures to protect sensitive information and ensure regulatory compliance. Requirement Proven experience as a Data Engineer, with expertise in building and optimizing data pipelines using PySpark , Scala, and Apache Spark. Hands-on experience with cloud platforms, particularly Azure, and proficiency in Azure services such as Azure Databricks, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL Database. Strong programming skills in Python and Scala, with experience in software development, version control, and CI/CD practices. Familiarity with data warehousing concepts, dimensional modeling, and relational databases (e.g., SQL Server, PostgreSQL, MySQL). Experience with big data technologies and frameworks (e.g., Hadoop, Hive, HBase) is a plus. Mandatory skill set s: Spark, Pyspark , Azure Preferred skill sets : Spark, Pyspark , Azure Years of experience required : 8 - 12 Education qualification : B.Tech / M.Tech / MBA / MCA Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Bachelor of Engineering, Master of Engineering, Master of Business Administration Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Data Science Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling {+ 32 more} Desired Languages (If blank, desired languages not specified) Travel Requirements Not Specified Available for Work Visa Sponsorship? No Government Clearance Required? No Job Posting End Date

Data Engineer Role Category: Programming & Design Job Location: Jaipur, Rajasthan on-site Experience Required: 3–6 Years About the Role We are looking for a highly skilled and motivated Data Engineer to join our team. You will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure that supports analytics, machine learning, and business intelligence initiatives across the company. Key Responsibilities Design, develop, and maintain robust ETL/ELT pipelines to ingest and process data from multiple sources. Build and maintain scalable and reliable data warehouses, data lakes, and data marts. Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver solutions. Ensure data quality, integrity, and security across all data systems. Optimize data pipeline performance and troubleshoot issues in a timely manner. Implement data governance and best practices in data management. Automate data validation, monitoring, and reporting processes. Required Skills and Qualifications Bachelor's or Master’s degree in Computer Science, Engineering, Information Systems, or related field. Proven experience (X+ years) as a Data Engineer or similar role. Strong programming skills in Python, Java, or Scala. Proficiency with SQL and working knowledge of relational databases (e.g., PostgreSQL, MySQL). Hands-on experience with big data technologies (e.g., Spark, Hadoop). Familiarity with cloud platforms such as AWS, GCP, or Azure (e.g., S3, Redshift, BigQuery, Data Factory). Experience with orchestration tools like Airflow or Prefect. Knowledge of data modeling, warehousing, and architecture design principles. Strong problem-solving skills and attention to detail.

When you join Verizon You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife. What You’ll Be Doing... Designing and Implementing ML Model pipelines (Batch and real-time) for efficient model training and serving/inference. Implementing and analyzing the performance of advanced algorithms (Specifically Deep Learning based ML Models). Solving the model inferencing failures/fallouts. Optimizing existing machine-learning Model Pipelines to ensure the training/inferencing is within the standard duration Collaborating effectively with cross-functional teams to understand business needs and deliver impactful solutions. Contributing to developing robust and scalable distributed computing systems for large-scale data processing. Designing, developing, and implementing innovative AI/ML solutions using Python, CI/CD, public cloud platforms Implementing model performance metrics pipeline for predictive models, covering different types of algorithms to adhere to Responsible AI. What We’re Looking For... You’ll need to have: Bachelor's degree or four or more years of work experience. Four or more years of relevant work experience. Experience in Batch Model Inferencing, Model-serving in Realtime. Knowledge on Frameworks such as BentoML TensorFlow Serving (TFX) or Triton. Solid expertise on GCP Cloud ML techstacks such as Bigquery, Data Proc, Airflow, Cloud Functions, Spanner, Data Flow. Very good experience on languages such as Python and PySpark. Expertise on Distributed computation and Multi-node distributed model training. Good understanding on GPU usage management. Experience on RAY Core and RAY Serve (batch and real-time models). Experience in CI/CD practices. Even better if you have one or more of the following: GCP Certifications or any Cloud Certification on AI/ML or Data w If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every “even better” qualification listed above. #AI&D Where you’ll be working In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager. Scheduled Weekly Hours 40 Equal Employment Opportunity Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics. Show more Show less

Job Summary: We are looking for a highly capable and automation-driven MLOps Engineer with 2+ years of experience in building and managing end-to-end ML infrastructure. This role focuses on operationalizing ML pipelines using tools like DVC, MLflow, Kubeflow, and Airflow, while ensuring efficient deployment, versioning, and monitoring of machine learning and Generative AI models across GPU-based cloud infrastructure (AWS/GCP). The ideal candidate will also have experience in multi-modal orchestration, model drift detection, and CI/CD for ML systems. Key Responsibilities: Develop, automate, and maintain scalable ML pipelines using tools such as Kubeflow, MLflow, Airflow, and DVC. Set up and manage CI/CD pipelines tailored to ML workflows, ensuring reliable model training, testing, and deployment. Containerize ML services using Docker and orchestrate them using Kubernetes in both development and production environments. Manage GPU infrastructure and cloud-based deployments (AWS, GCP) for high-performance training and inference. Integrate Hugging Face models and multi-modal AI systems into robust deployment frameworks. Monitor deployed models for drift, performance degradation, and inference bottlenecks, enabling continuous feedback and retraining. Ensure proper model versioning, lineage, and reproducibility for audit and compliance. Collaborate with data scientists, ML engineers, and DevOps teams to build reliable and efficient MLOps systems. Support Generative AI model deployment with scalable architecture and automation-first practices. Qualifications: 2+ years of experience in MLOps, DevOps for ML, or Machine Learning Engineering. Hands-on experience with MLflow, DVC, Kubeflow, Airflow, and CI/CD tools for ML. Proficiency in containerization and orchestration using Docker and Kubernetes. Experience with GPU infrastructure, including setup, scaling, and cost optimization on AWS or GCP. Familiarity with model monitoring, drift detection, and production-grade deployment pipelines. Good understanding of model lifecycle management, reproducibility, and compliance. Preferred Qualifications : Experience deploying Generative AI or multi-modal models in production. Knowledge of Hugging Face Transformers, model quantization, and resource-efficient inference. Familiarity with MLOps frameworks and observability stacks. Experience with security, governance, and compliance in ML environments. Location-Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad