252 Technical Architect Jobs - Page 10

Encora is looking for Technical Architect to join our dynamic team and embark on a rewarding career journey. Providing technical leadership and guidance to software development teamsDesigning and developing software solutions that meet business requirements and align with enterprise architecture standardsCollaborating with project managers, product owners, and other stakeholders to understand requirements and ensure software solutions meet customer needsConducting technology research and evaluation to identify new technologies and solutions that can improve software development processesDeveloping and maintaining software architecture and design documentationProviding technical mentorship to junior software developersEnsuring that software solutions are developed with high levels of quality, performance, and securityParticipating in code reviews to ensure code quality and adherence to best practicesCommunicating project status and progress to stakeholders, including project managers and customersExcellent communication and interpersonal skillsStrong understanding of software architecture and design patterns

Exp : Total exp should be 12+ Years. Position type : Contract position for 6 months extendable. Location : Pune - Hybrid Work module. Responsibilities : - Lead the development of data visualization and analytics solutions, focusing on creating efficient and scalable Power BI reports and dashboards. - Strong background in data modelling, data transformation, and business intelligence (BI) best practices, with a passion for converting complex data into actionable insights. - Designing and implementing Power BI solutions for complex business requirements. - Design, develop, and deploy end-to-end Power BI solutions to meet organizational needs. - Collaborate with business stakeholders to understand reporting requirements and key performance metrics. - Design, develop, and optimize Power BI data models, reports, and dashboards to support analytics needs. - Create effective data visualization strategies to enhance decision-making processes. - Work with data engineering teams to set up and manage data extraction, transformation, and loading (ETL) processes. - Develop data models that ensure data accuracy, consistency, and optimal performance. - Implement row-level security and application security in Power BI. - Lead and mentor other team members in Power BI and data visualization best practices. - Conduct performance tuning and optimization of Power BI reports and datasets.

rovidesdeterminesprioritisationthatTechnical Architect Role Overview: We are looking for a seasoned Technical Architect to lead the design and development of scalable, robust, and secure software systems. You will work closely with engineering, product, and business teams to translate requirements into high-level technical solutions and guide engineering teams through implementation. This is a strategic role combining hands-on coding with architectural oversight and technology leadership. Looking for 10+ years of experience and 5+ years of experience on an Architect role. Project Objectives: Join a fast-paced incubation studio who takes in new business ideas and/or feature ideas, and determine their technical feasibility, and provide your input and guidance from your functional area of expertise. The key objective initially will be to bring your incubation studio experiences to the table to be an instrumental player in defining and/or refining the studio operating model design. Then continue to run the backlog of new ideas through the incubator while continuing to seek ways to improve studio throughput. Establish a scalable, repeatable operating model for an Idea Incubator Studio. Integrate Agentic AI capabilities to augment ideation, research, product design, and decision-making processes. Define and implement standard workflows and governance for intake, prioritization, validation, and handoff of ideas. Enable business product owners to co-create with the studio via structured frameworks and low-friction engagement models. Ensure transferability of incubated innovations into core operational or product teams. Role & responsibilities: Define and own the overall software architecture, ensuring alignment with business goals, scalability, and best practices. Evaluate and recommend tools, technologies, and processes to ensure the highest level of system performance, availability, and reliability. Collaborate with product managers and stakeholders to assess technical feasibility, define roadmaps, and make build vs. buy decisions. Provide guidance and mentorship to developers, conducting code reviews and ensuring adherence to coding standards. Design and document high-level architectural plans, APIs, data flows, and system integration strategies. Lead the selection of cloud platforms, data stores, frameworks, and development methodologies. Ensure security, compliance, and risk management are factored into architectural decisions. Troubleshoot and resolve critical technical issues across the stack. Required Skills: Demonstrated experience with 10+ years of software engineering experience, with 5+ years in an architecture or technical leadership role. Dev Environment Experience in: Azure Cloud Services (AKS, Azure Store); Open Source (MERN); Insights Event Log Monitoring Dev Stack Experience with Next.JS; Express; Node.JS; REACT; Rest Bachelors or Masters degree in Computer Science, Engineering, or a related field. Proven experience designing and deploying scalable, distributed systems (microservices, serverless, or monolithic). Strong proficiency in one or more tech stacks (e.g., Java/.NET, Node.js, Python, Go) and modern frontend frameworks (e.g., Angular, React, Vue). Hands-on experience with cloud platforms (AWS, Azure, GCP) and cloud-native services. In-depth knowledge of databases (SQL and NoSQL), caching, CI/CD pipelines, and DevOps practices. Excellent communication skills and the ability to present complex technical concepts to both technical and non-technical stakeholders. Preferred candidate profile: Experience or familiarity with the following development AI tools: DocuWriter. Ai – Document Code; Artefact – Data; Aporia – Security; Devin. Ai – Coding Assistance; GitHub Copilot – Coding Assistance Experience with containerization (Docker, Kubernetes). Familiarity with enterprise integration patterns, messaging systems, and event-driven architecture. Exposure to data engineering, AI/ML, or big data tools is a plus.

Role : Snowflake Practice Lead / Architect / Solution Architect Exp : 13+ Years Work Location : Hyderabad Position Overview : We are seeking a highly skilled and experienced - Snowflake Practice Lead- to drive our data strategy, architecture, and implementation using Snowflake. This leadership role requires a deep understanding of Snowflake's cloud data platform, data engineering best practices, and enterprise data management. The ideal candidate will be responsible for defining best practices, leading a team of Snowflake professionals, and driving successful Snowflake implementations for clients. Key Responsibilities : Leadership & Strategy : - Define and drive the Snowflake practice strategy, roadmap, and best practices. - Act as the primary subject matter expert (SME) for Snowflake architecture, implementation, and optimization. - Collaborate with stakeholders to understand business needs and align data strategies accordingly. Technical Expertise & Solutioning : - Design and implement scalable, high-performance data architectures using - Snowflake- . - Develop best practices for data ingestion, transformation, modeling, and security- within Snowflake. - Guide clients on Snowflake migrations, ensuring a seamless transition from legacy systems. - Optimize - query performance, storage utilization, and cost efficiency- in Snowflake environments. Team Leadership & Mentorship : - Lead and mentor a team of Snowflake developers, data engineers, and architects. - Provide technical guidance, conduct code reviews, and establish best practices for Snowflake development. - Train internal teams and clients on Snowflake capabilities, features, and emerging trends. Client & Project Management : - Engage with clients to understand business needs and design tailored Snowflake solutions. - Lead - end-to-end Snowflake implementation projects , ensuring quality and timely delivery. - Work closely with - data scientists, analysts, and business stakeholders- to maximize data utilization. Required Skills & Experience : - 10+ years of experience- in data engineering, data architecture, or cloud data platforms. - 5+ years of hands-on experience with Snowflake in large-scale enterprise environments. - Strong expertise in SQL, performance tuning, and cloud-based data solutions. - Experience with ETL/ELT processes, data pipelines, and data integration tools- (e.g., Talend, Matillion, dbt, Informatica). - Proficiency in cloud platforms such as AWS, Azure, or GCP, particularly their integration with Snowflake. - Knowledge of data security, governance, and compliance best practices . - Strong leadership, communication, and client-facing skills. - Experience in migrating from traditional data warehouses (Oracle, Teradata, SQL Server) to Snowflake. - Familiarity with Python, Spark, or other big data technologies is a plus. Preferred Qualifications : - Snowflake SnowPro Certification- (e.g., SnowPro Core, Advanced Architect, Data Engineer). - Experience in building data lakes, data marts, and real-time analytics solutions- . - Hands-on experience with DevOps, CI/CD pipelines, and Infrastructure as Code (IaC)- in Snowflake environments. Why Join Us? - Opportunity to lead cutting-edge Snowflake implementations- in a dynamic, fast-growing environment. - Work with top-tier clients across industries, solving complex data challenges. - Continuous learning and growth opportunities in cloud data technologies. - Competitive compensation, benefits, and a collaborative work culture.

Seeking a highly experienced and dynamic Senior Technology Architect / Presales professional / Practice Professional to join team. The ideal candidate will have a strong background in Java technologies, minimum of 17+ years of software engineering experience combined with excellent presales and leadership skills. Candidate must possess a deep understanding of system architecture, and a strong proficiency in Cloud (any of AWS/Azure/GCP/Oracle), Java, Spring Boot, UI framework such as Angular/React, Microservices architecture, Distributed computing, Software Engineering principles, Enterprise Architecture, DevSecOps, AI/ML and Data modelling. This role is pivotal in driving our technical solutions, business support and supporting the sales process with strategic insights and exceptional communication skills. Role & responsibilities Key Responsibilities: Technical Expertise: Design and develop scalable, high-performance architectural solutions tailored to client needs. o Create detailed technical documentation and architectural blueprints. o Hands-on and provide technical expertise in areas such as Cloud, Java, Spring Boot, System Design and Architecture, Enterprise Architecture o Provide deep technical expertise in Java technologies, frameworks, and solutions. o Lead the design and development of Java-based solutions and proofs of concept (POCs) to showcase product capabilities. Technology Thought Leadership and Guidance: Provide expert technical leadership and guidance to development teams across project lifecycles o Conduct thorough design reviews, code reviews, ensuring adherence to best practices and coding standards, as and when necessary. o Collaborating with sales and marketing teams to develop and refine software solutions and service offerings o Representing organization in technical forums, conferences or community engagements o Engaging with partners and vendors to explore complementary technologies, tools, and frameworks that can enhance the organizations Java offerings o Mentor and support junior architects and developers, promoting a culture of excellence and continuous improvement. o Show technology thought leadership by contributing to position papers, accelerators, IPs, Patents etc. o Mentor and develop the presales team, fostering a culture of continuous learning and professional growth. o Facilitate knowledge sharing and best practices within the team. Sales Support: Collaborate with the sales team to understand customer needs and develop tailored technical solutions. Internal - General Use o Develop and implement presales strategies to support business objectives and drive revenue growth. o Prepare and deliver compelling technical presentations, demonstrations, and workshops to prospective clients. o Develop proof-of-concept projects to illustrate the technical viability and advantages of proposed solutions. o Own the technical solution for proposals end to end, create estimates, assist in commercials for the proposals o Assist in the preparation of proposals, RFPs/RFIs, and other sales documents. o Participate and Lead the customer presentations, visits, Orals to represent technical solution and provide prompt response on the customer technical queries Customer Engagement: Engage with customers and partners to gather feedback and ensure alignment on technical solutions. o Build and maintain strong relationships with key stakeholders to facilitate smooth project execution and customer satisfaction. o Develop proof-of-concept projects to illustrate the technical viability and advantages of proposed solutions. o Address client queries and concerns promptly, ensuring high levels of client satisfaction and retention. Innovation, Market and Industry Awareness: Stay abreast of the latest trends and advancements in Java technologies and industry best practices. o Provide insights and recommendations to enhance our product offerings and maintain competitive advantage. Qualifications: Education: Bachelors or Masters degree in Computer Science, Information Technology, or a related field. Experience: o Extensive experience in a practice role, with a strong focus on Java technologies. o Proven track record of contributing in presales team. o Must to have expertise in Java technologies, frameworks (e.g., Spring, Hibernate), and design patterns is a must. o Good Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and microservices architecture is must. Skills: o Exceptional communication and presentation skills, with the ability to articulate complex technical concepts to diverse audiences. o Strong analytical and problem-solving abilities and a customer-centric mindset. o Proficiency in creating technical documentation and solution diagrams. o Strong leadership and team management skills. Additional Needs: o Willingness to travel as necessary to meet with clients and attend industry events. o Proactive, self-motivated, and passionate about technology and innovation. Certifications: o Relevant Java and cloud certifications are a plus.

Role : Principal ML Ops Architect Responsibilities : 1. Strategic Leadership :a. Define and drive the overall ML Ops strategy and roadmap for the organization, aligning it with business objectives and technical capabilities.b. Oversee the design, development, and implementation of ML Ops platforms, frameworks, and processes.c. Foster a culture of innovation and continuous improvement within the ML Ops team. 2. Technical Architecture :a. Design and implement scalable, reliable, and efficient ML Ops architectures.b. Select and integrate appropriate tools, technologies, and frameworks to support the ML lifecycle.c. Ensure compliance with industry best practices and standards for ML Ops. 3. Team Management :a. Lead and mentor a team of ML Ops engineers and architects.b. Foster collaboration and knowledge sharing among team members.c. Provide technical guidance and support to data scientists and engineers. 4. Innovation and Research :a. Stay up-to-date with emerging ML Ops trends and technologies.b. Research and evaluate new tools and techniques to enhance ML Ops capabilities.c. Contribute to the development of innovative ML Ops solutions. Minimum Required Skills :- 11+ years of experience preferred. - Proven track record of designing and implementing large-scale ML pipelines and infrastructure.- Experience with distributed computing frameworks (Spark, Hadoop)- Knowledge of graph databases and auto ML libraries- Bachelor's / Master's degree in computer science, analytics, mathematics, statistics - Strong experience in Python, SQL.- Solid understanding and knowledge of containerization technologies (Docker, Kubernetes).- Proficient in Experience in CI/CD pipelines, model monitoring, and MLOps platforms (Kubeflow, MLFlow)- Proficiency in cloud platforms, containerization, and ML frameworks (TensorFlow, PyTorch). - Certifications in cloud platforms or ML technologies can be a plus.- Extensive experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).- Strong problem-solving and analytical skills.- Ability to plan, execute and take ownership of task. ML Ops / MLOps Architect- Azure DevOps- Docker- Kubernetes- TensorFlow- MLFlow- Pipeline- Machine Learning Platform Engineer- Data Science Platform Engineer- DevOps Engineer (with ML focus)- AI Engineer- Data Engineer- Cloud Engineer (with ML focus)- Software Engineer (with ML focus)- Model Deployment Specialist- MLOps Architect- CI/CD- PyTorch- Scikit-learn- Cloud Computing- Big Data- Azure- Azure Machine Learning- GCP- Vertex AI- AWS- Amazon SageMaker

Role : Principal ML Ops Architect Responsibilities : 1. Strategic Leadership :a. Define and drive the overall ML Ops strategy and roadmap for the organization, aligning it with business objectives and technical capabilities.b. Oversee the design, development, and implementation of ML Ops platforms, frameworks, and processes.c. Foster a culture of innovation and continuous improvement within the ML Ops team. 2. Technical Architecture :a. Design and implement scalable, reliable, and efficient ML Ops architectures.b. Select and integrate appropriate tools, technologies, and frameworks to support the ML lifecycle.c. Ensure compliance with industry best practices and standards for ML Ops. 3. Team Management :a. Lead and mentor a team of ML Ops engineers and architects.b. Foster collaboration and knowledge sharing among team members.c. Provide technical guidance and support to data scientists and engineers. 4. Innovation and Research :a. Stay up-to-date with emerging ML Ops trends and technologies.b. Research and evaluate new tools and techniques to enhance ML Ops capabilities.c. Contribute to the development of innovative ML Ops solutions. Minimum Required Skills :- 11+ years of experience preferred. - Proven track record of designing and implementing large-scale ML pipelines and infrastructure.- Experience with distributed computing frameworks (Spark, Hadoop)- Knowledge of graph databases and auto ML libraries- Bachelor's / Master's degree in computer science, analytics, mathematics, statistics - Strong experience in Python, SQL.- Solid understanding and knowledge of containerization technologies (Docker, Kubernetes).- Proficient in Experience in CI/CD pipelines, model monitoring, and MLOps platforms (Kubeflow, MLFlow)- Proficiency in cloud platforms, containerization, and ML frameworks (TensorFlow, PyTorch). - Certifications in cloud platforms or ML technologies can be a plus.- Extensive experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).- Strong problem-solving and analytical skills.- Ability to plan, execute and take ownership of task. ML Ops / MLOps Architect- Azure DevOps- Docker- Kubernetes- TensorFlow- MLFlow- Pipeline- Machine Learning Platform Engineer- Data Science Platform Engineer- DevOps Engineer (with ML focus)- AI Engineer- Data Engineer- Cloud Engineer (with ML focus)- Software Engineer (with ML focus)- Model Deployment Specialist- MLOps Architect- CI/CD- PyTorch- Scikit-learn- Cloud Computing- Big Data- Azure- Azure Machine Learning- GCP- Vertex AI- AWS- Amazon SageMaker

Role : Principal ML Ops Architect Responsibilities : 1. Strategic Leadership : a. Define and drive the overall ML Ops strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of ML Ops platforms, frameworks, and processes. c. Foster a culture of innovation and continuous improvement within the ML Ops team. 2. Technical Architecture : a. Design and implement scalable, reliable, and efficient ML Ops architectures. b. Select and integrate appropriate tools, technologies, and frameworks to support the ML lifecycle. c. Ensure compliance with industry best practices and standards for ML Ops. 3. Team Management : a. Lead and mentor a team of ML Ops engineers and architects. b. Foster collaboration and knowledge sharing among team members. c. Provide technical guidance and support to data scientists and engineers. 4. Innovation and Research : a. Stay up-to-date with emerging ML Ops trends and technologies. b. Research and evaluate new tools and techniques to enhance ML Ops capabilities. c. Contribute to the development of innovative ML Ops solutions. Minimum Required Skills : - 11+ years of experience preferred. - Proven track record of designing and implementing large-scale ML pipelines and infrastructure. - Experience with distributed computing frameworks (Spark, Hadoop) - Knowledge of graph databases and auto ML libraries - Bachelor's / Master's degree in computer science, analytics, mathematics, statistics - Strong experience in Python, SQL. - Solid understanding and knowledge of containerization technologies (Docker, Kubernetes). - Proficient in Experience in CI/CD pipelines, model monitoring, and MLOps platforms (Kubeflow, MLFlow) - Proficiency in cloud platforms, containerization, and ML frameworks (TensorFlow, PyTorch). - Certifications in cloud platforms or ML technologies can be a plus. - Extensive experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). - Strong problem-solving and analytical skills. - Ability to plan, execute and take ownership of task. Keywords : - ML Ops / MLOps Architect - Azure DevOps - Docker - Kubernetes - TensorFlow - MLFlow - Pipeline - Machine Learning Platform Engineer - Data Science Platform Engineer - DevOps Engineer (with ML focus) - AI Engineer - Data Engineer - Cloud Engineer (with ML focus) - Software Engineer (with ML focus) - Model Deployment Specialist - MLOps Architect - CI/CD - PyTorch - Scikit-learn - Cloud Computing - Big Data - Azure - Azure Machine Learning - GCP - Vertex AI - AWS - Amazon SageMaker

Role : Principal ML Ops Architect Responsibilities : 1. Strategic Leadership : a. Define and drive the overall ML Ops strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of ML Ops platforms, frameworks, and processes. c. Foster a culture of innovation and continuous improvement within the ML Ops team. 2. Technical Architecture : a. Design and implement scalable, reliable, and efficient ML Ops architectures. b. Select and integrate appropriate tools, technologies, and frameworks to support the ML lifecycle. c. Ensure compliance with industry best practices and standards for ML Ops. 3. Team Management : a. Lead and mentor a team of ML Ops engineers and architects. b. Foster collaboration and knowledge sharing among team members. c. Provide technical guidance and support to data scientists and engineers. 4. Innovation and Research : a. Stay up-to-date with emerging ML Ops trends and technologies. b. Research and evaluate new tools and techniques to enhance ML Ops capabilities. c. Contribute to the development of innovative ML Ops solutions. Minimum Required Skills : - 11+ years of experience preferred. - Proven track record of designing and implementing large-scale ML pipelines and infrastructure. - Experience with distributed computing frameworks (Spark, Hadoop) - Knowledge of graph databases and auto ML libraries - Bachelor's / Master's degree in computer science, analytics, mathematics, statistics - Strong experience in Python, SQL. - Solid understanding and knowledge of containerization technologies (Docker, Kubernetes). - Proficient in Experience in CI/CD pipelines, model monitoring, and MLOps platforms (Kubeflow, MLFlow) - Proficiency in cloud platforms, containerization, and ML frameworks (TensorFlow, PyTorch). - Certifications in cloud platforms or ML technologies can be a plus. - Extensive experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). - Strong problem-solving and analytical skills. - Ability to plan, execute and take ownership of task. Keywords : - ML Ops / MLOps Architect - Azure DevOps - Docker - Kubernetes - TensorFlow - MLFlow - Pipeline - Machine Learning Platform Engineer - Data Science Platform Engineer - DevOps Engineer (with ML focus) - AI Engineer - Data Engineer - Cloud Engineer (with ML focus) - Software Engineer (with ML focus) - Model Deployment Specialist - MLOps Architect - CI/CD - PyTorch - Scikit-learn - Cloud Computing - Big Data - Azure - Azure Machine Learning - GCP - Vertex AI - AWS - Amazon SageMaker

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall ML Ops strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of ML Ops platforms, frameworks, and processes. c. Foster a culture of innovation and continuous improvement within the ML Ops team. 2. Technical Architecture : a. Design and implement scalable, reliable, and efficient ML Ops architectures. b. Select and integrate appropriate tools, technologies, and frameworks to support the ML lifecycle. c. Ensure compliance with industry best practices and standards for ML Ops. 3. Team Management : a. Lead and mentor a team of ML Ops engineers and architects. b. Foster collaboration and knowledge sharing among team members. c. Provide technical guidance and support to data scientists and engineers. 4. Innovation and Research : a. Stay up-to-date with emerging ML Ops trends and technologies. b. Research and evaluate new tools and techniques to enhance ML Ops capabilities. c. Contribute to the development of innovative ML Ops solutions. Minimum Required Skills : - 11+ years of experience preferred. - Proven track record of designing and implementing large-scale ML pipelines and infrastructure. - Experience with distributed computing frameworks (Spark, Hadoop) - Knowledge of graph databases and auto ML libraries - Bachelor's / Master's degree in computer science, analytics, mathematics, statistics - Strong experience in Python, SQL. - Solid understanding and knowledge of containerization technologies (Docker, Kubernetes). - Proficient in Experience in CI/CD pipelines, model monitoring, and MLOps platforms (Kubeflow, MLFlow) - Proficiency in cloud platforms, containerization, and ML frameworks (TensorFlow, PyTorch). - Certifications in cloud platforms or ML technologies can be a plus. - Extensive experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). - Strong problem-solving and analytical skills. - Ability to plan, execute and take ownership of task. Keywords : - ML Ops / MLOps Architect - Azure DevOps - Docker - Kubernetes - TensorFlow - MLFlow - Pipeline - Machine Learning Platform Engineer - Data Science Platform Engineer - DevOps Engineer (with ML focus) - AI Engineer - Data Engineer - Cloud Engineer (with ML focus) - Software Engineer (with ML focus) - Model Deployment Specialist - MLOps Architect - CI/CD - PyTorch - Scikit-learn - Cloud Computing - Big Data - Azure - Azure Machine Learning - GCP - Vertex AI - AWS - Amazon SageMaker

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall ML Ops strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of ML Ops platforms, frameworks, and processes. c. Foster a culture of innovation and continuous improvement within the ML Ops team. 2. Technical Architecture : a. Design and implement scalable, reliable, and efficient ML Ops architectures. b. Select and integrate appropriate tools, technologies, and frameworks to support the ML lifecycle. c. Ensure compliance with industry best practices and standards for ML Ops. 3. Team Management : a. Lead and mentor a team of ML Ops engineers and architects. b. Foster collaboration and knowledge sharing among team members. c. Provide technical guidance and support to data scientists and engineers. 4. Innovation and Research : a. Stay up-to-date with emerging ML Ops trends and technologies. b. Research and evaluate new tools and techniques to enhance ML Ops capabilities. c. Contribute to the development of innovative ML Ops solutions. Minimum Required Skills : - 11+ years of experience preferred. - Proven track record of designing and implementing large-scale ML pipelines and infrastructure. - Experience with distributed computing frameworks (Spark, Hadoop) - Knowledge of graph databases and auto ML libraries - Bachelor's / Master's degree in computer science, analytics, mathematics, statistics - Strong experience in Python, SQL. - Solid understanding and knowledge of containerization technologies (Docker, Kubernetes). - Proficient in Experience in CI/CD pipelines, model monitoring, and MLOps platforms (Kubeflow, MLFlow) - Proficiency in cloud platforms, containerization, and ML frameworks (TensorFlow, PyTorch). - Certifications in cloud platforms or ML technologies can be a plus. - Extensive experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). - Strong problem-solving and analytical skills. - Ability to plan, execute and take ownership of task. Keywords : - ML Ops / MLOps Architect - Azure DevOps - Docker - Kubernetes - TensorFlow - MLFlow - Pipeline - Machine Learning Platform Engineer - Data Science Platform Engineer - DevOps Engineer (with ML focus) - AI Engineer - Data Engineer - Cloud Engineer (with ML focus) - Software Engineer (with ML focus) - Model Deployment Specialist - MLOps Architect - CI/CD - PyTorch - Scikit-learn - Cloud Computing - Big Data - Azure - Azure Machine Learning - GCP - Vertex AI - AWS - Amazon SageMaker

Role : Principal ML Ops ArchitectResponsibilities :1. Strategic Leadership :a. Define and drive the overall ML Ops strategy and roadmap for the organization, aligning it with business objectives and technical capabilities.b. Oversee the design, development, and implementation of ML Ops platforms, frameworks, and processes.c. Foster a culture of innovation and continuous improvement within the ML Ops team. 2. Technical Architecture :a. Design and implement scalable, reliable, and efficient ML Ops architectures.b. Select and integrate appropriate tools, technologies, and frameworks to support the ML lifecycle.c. Ensure compliance with industry best practices and standards for ML Ops. 3. Team Management :a. Lead and mentor a team of ML Ops engineers and architects.b. Foster collaboration and knowledge sharing among team members.c. Provide technical guidance and support to data scientists and engineers. 4. Innovation and Research :a. Stay up-to-date with emerging ML Ops trends and technologies.b. Research and evaluate new tools and techniques to enhance ML Ops capabilities.c. Contribute to the development of innovative ML Ops solutions. Minimum Required Skills :- 11+ years of experience preferred. - Proven track record of designing and implementing large-scale ML pipelines and infrastructure.- Experience with distributed computing frameworks (Spark, Hadoop)- Knowledge of graph databases and auto ML libraries- Bachelor's / Master's degree in computer science, analytics, mathematics, statistics- Strong experience in Python, SQL.- Solid understanding and knowledge of containerization technologies (Docker, Kubernetes).- Proficient in Experience in CI/CD pipelines, model monitoring, and MLOps platforms (Kubeflow, MLFlow)- Proficiency in cloud platforms, containerization, and ML frameworks (TensorFlow, PyTorch).- Certifications in cloud platforms or ML technologies can be a plus. - Extensive experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).- Strong problem-solving and analytical skills.- Ability to plan, execute and take ownership of task.Keywords :- ML Ops / MLOps Architect- Azure DevOps- Docker- Kubernetes- TensorFlow- MLFlow- Pipeline- Machine Learning Platform Engineer- Data Science Platform Engineer- DevOps Engineer (with ML focus)- AI Engineer- Data Engineer- Cloud Engineer (with ML focus)- Software Engineer (with ML focus)- Model Deployment Specialist- MLOps Architect- CI/CD- PyTorch- Scikit-learn- Cloud Computing- Big Data- Azure- Azure Machine Learning- GCP- Vertex AI- AWS- Amazon SageMaker

Role : Principal ML Ops Architect Responsibilities : 1. Strategic Leadership : a. Define and drive the overall ML Ops strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of ML Ops platforms, frameworks, and processes. c. Foster a culture of innovation and continuous improvement within the ML Ops team. 2. Technical Architecture : a. Design and implement scalable, reliable, and efficient ML Ops architectures. b. Select and integrate appropriate tools, technologies, and frameworks to support the ML lifecycle. c. Ensure compliance with industry best practices and standards for ML Ops. 3. Team Management : a. Lead and mentor a team of ML Ops engineers and architects. b. Foster collaboration and knowledge sharing among team members. c. Provide technical guidance and support to data scientists and engineers. 4. Innovation and Research : a. Stay up-to-date with emerging ML Ops trends and technologies. b. Research and evaluate new tools and techniques to enhance ML Ops capabilities. c. Contribute to the development of innovative ML Ops solutions. Minimum Required Skills : - 11+ years of experience preferred. - Proven track record of designing and implementing large-scale ML pipelines and infrastructure. - Experience with distributed computing frameworks (Spark, Hadoop) - Knowledge of graph databases and auto ML libraries - Bachelor's / Master's degree in computer science, analytics, mathematics, statistics - Strong experience in Python, SQL. - Solid understanding and knowledge of containerization technologies (Docker, Kubernetes). - Proficient in Experience in CI/CD pipelines, model monitoring, and MLOps platforms (Kubeflow, MLFlow) - Proficiency in cloud platforms, containerization, and ML frameworks (TensorFlow, PyTorch). - Certifications in cloud platforms or ML technologies can be a plus. - Extensive experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). - Strong problem-solving and analytical skills. - Ability to plan, execute and take ownership of task. Keywords : - ML Ops / MLOps Architect - Azure DevOps - Docker - Kubernetes - TensorFlow - MLFlow - Pipeline - Machine Learning Platform Engineer - Data Science Platform Engineer - DevOps Engineer (with ML focus) - AI Engineer - Data Engineer - Cloud Engineer (with ML focus) - Software Engineer (with ML focus) - Model Deployment Specialist - MLOps Architect - CI/CD - PyTorch - Scikit-learn - Cloud Computing - Big Data - Azure - Azure Machine Learning - GCP - Vertex AI - AWS - Amazon SageMaker

Role : Principal ML Ops Architect Responsibilities : 1. Strategic Leadership : a. Define and drive the overall ML Ops strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of ML Ops platforms, frameworks, and processes. c. Foster a culture of innovation and continuous improvement within the ML Ops team. 2. Technical Architecture : a. Design and implement scalable, reliable, and efficient ML Ops architectures. b. Select and integrate appropriate tools, technologies, and frameworks to support the ML lifecycle. c. Ensure compliance with industry best practices and standards for ML Ops. 3. Team Management : a. Lead and mentor a team of ML Ops engineers and architects. b. Foster collaboration and knowledge sharing among team members. c. Provide technical guidance and support to data scientists and engineers. 4. Innovation and Research : a. Stay up-to-date with emerging ML Ops trends and technologies. b. Research and evaluate new tools and techniques to enhance ML Ops capabilities. c. Contribute to the development of innovative ML Ops solutions. Minimum Required Skills : - 11+ years of experience preferred. - Proven track record of designing and implementing large-scale ML pipelines and infrastructure. - Experience with distributed computing frameworks (Spark, Hadoop) - Knowledge of graph databases and auto ML libraries - Bachelor's / Master's degree in computer science, analytics, mathematics, statistics - Strong experience in Python, SQL. - Solid understanding and knowledge of containerization technologies (Docker, Kubernetes). - Proficient in Experience in CI/CD pipelines, model monitoring, and MLOps platforms (Kubeflow, MLFlow) - Proficiency in cloud platforms, containerization, and ML frameworks (TensorFlow, PyTorch). - Certifications in cloud platforms or ML technologies can be a plus. - Extensive experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). - Strong problem-solving and analytical skills. - Ability to plan, execute and take ownership of task. Keywords : - ML Ops / MLOps Architect - Azure DevOps - Docker - Kubernetes - TensorFlow - MLFlow - Pipeline - Machine Learning Platform Engineer - Data Science Platform Engineer - DevOps Engineer (with ML focus) - AI Engineer - Data Engineer - Cloud Engineer (with ML focus) - Software Engineer (with ML focus) - Model Deployment Specialist - MLOps Architect - CI/CD - PyTorch - Scikit-learn - Cloud Computing - Big Data - Azure - Azure Machine Learning - GCP - Vertex AI - AWS - Amazon SageMaker

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall ML Ops strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of ML Ops platforms, frameworks, and processes. c. Foster a culture of innovation and continuous improvement within the ML Ops team. 2. Technical Architecture : a. Design and implement scalable, reliable, and efficient ML Ops architectures. b. Select and integrate appropriate tools, technologies, and frameworks to support the ML lifecycle. c. Ensure compliance with industry best practices and standards for ML Ops. 3. Team Management : a. Lead and mentor a team of ML Ops engineers and architects. b. Foster collaboration and knowledge sharing among team members. c. Provide technical guidance and support to data scientists and engineers. 4. Innovation and Research : a. Stay up-to-date with emerging ML Ops trends and technologies. b. Research and evaluate new tools and techniques to enhance ML Ops capabilities. c. Contribute to the development of innovative ML Ops solutions. Minimum Required Skills : - 11+ years of experience preferred. - Proven track record of designing and implementing large-scale ML pipelines and infrastructure. - Experience with distributed computing frameworks (Spark, Hadoop) - Knowledge of graph databases and auto ML libraries - Bachelor's / Master's degree in computer science, analytics, mathematics, statistics - Strong experience in Python, SQL. - Solid understanding and knowledge of containerization technologies (Docker, Kubernetes). - Proficient in Experience in CI/CD pipelines, model monitoring, and MLOps platforms (Kubeflow, MLFlow) - Proficiency in cloud platforms, containerization, and ML frameworks (TensorFlow, PyTorch). - Certifications in cloud platforms or ML technologies can be a plus. - Extensive experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). - Strong problem-solving and analytical skills. - Ability to plan, execute and take ownership of task. Keywords : - ML Ops / MLOps Architect - Azure DevOps - Docker - Kubernetes - TensorFlow - MLFlow - Pipeline - Machine Learning Platform Engineer - Data Science Platform Engineer - DevOps Engineer (with ML focus) - AI Engineer - Data Engineer - Cloud Engineer (with ML focus) - Software Engineer (with ML focus) - Model Deployment Specialist - MLOps Architect - CI/CD - PyTorch - Scikit-learn - Cloud Computing - Big Data - Azure - Azure Machine Learning - GCP - Vertex AI - AWS - Amazon SageMaker

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall ML Ops strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of ML Ops platforms, frameworks, and processes. c. Foster a culture of innovation and continuous improvement within the ML Ops team. 2. Technical Architecture : a. Design and implement scalable, reliable, and efficient ML Ops architectures. b. Select and integrate appropriate tools, technologies, and frameworks to support the ML lifecycle. c. Ensure compliance with industry best practices and standards for ML Ops. 3. Team Management : a. Lead and mentor a team of ML Ops engineers and architects. b. Foster collaboration and knowledge sharing among team members. c. Provide technical guidance and support to data scientists and engineers. 4. Innovation and Research : a. Stay up-to-date with emerging ML Ops trends and technologies. b. Research and evaluate new tools and techniques to enhance ML Ops capabilities. c. Contribute to the development of innovative ML Ops solutions. Minimum Required Skills : - 11+ years of experience preferred. - Proven track record of designing and implementing large-scale ML pipelines and infrastructure. - Experience with distributed computing frameworks (Spark, Hadoop) - Knowledge of graph databases and auto ML libraries - Bachelor's / Master's degree in computer science, analytics, mathematics, statistics - Strong experience in Python, SQL. - Solid understanding and knowledge of containerization technologies (Docker, Kubernetes). - Proficient in Experience in CI/CD pipelines, model monitoring, and MLOps platforms (Kubeflow, MLFlow) - Proficiency in cloud platforms, containerization, and ML frameworks (TensorFlow, PyTorch). - Certifications in cloud platforms or ML technologies can be a plus. - Extensive experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). - Strong problem-solving and analytical skills. - Ability to plan, execute and take ownership of task. Keywords : - ML Ops / MLOps Architect - Azure DevOps - Docker - Kubernetes - TensorFlow - MLFlow - Pipeline - Machine Learning Platform Engineer - Data Science Platform Engineer - DevOps Engineer (with ML focus) - AI Engineer - Data Engineer - Cloud Engineer (with ML focus) - Software Engineer (with ML focus) - Model Deployment Specialist - MLOps Architect - CI/CD - PyTorch - Scikit-learn - Cloud Computing - Big Data - Azure - Azure Machine Learning - GCP - Vertex AI - AWS - Amazon SageMaker

Role & responsibilities : Project Role : Business Process Architect Project Role Description : Design business processes, including characteristics and key performance indicators (KPIs), to meet process and functional requirements. Work closely with the Application Architect to create the process blueprint and establish business process requirements to drive out application requirements and metrics. Assist in quality management reviews, ensure all business and design requirements are met. Educate stakeholders to ensure a complete understanding of the designs. Must have skills : Microsoft Dynamics 365 ERP Technical/AX Technical/F&O Technical Good to have skills : NA Minimum 12 year(s) of experience is required Educational Qualification : Should be a Graduate Summary: As a Business Process Architect, you will be responsible for designing business processes, including characteristics and key performance indicators (KPIs), to meet process and functional requirements. Your typical day will involve working closely with the Application Architect to create the process blueprint and establish business process requirements to drive out application requirements and metrics. Roles & Responsibilities: - Design business processes, including characteristics and key performance indicators (KPIs), to meet process and functional requirements. - Work closely with the Application Architect to create the process blueprint and establish business process requirements to drive out application requirements and metrics. - Assist in quality management reviews, ensure all business and design requirements are met. - Educate stakeholders to ensure a complete understanding of the designs. Professional & Technical Skills: - Must To Have Skills: 12 years of experience in Microsoft Dynamics 365 ERP Technical. - Good To Have Skills: Experience in quality management reviews. - Strong understanding of business processes and functional requirements. - Experience in educating stakeholders to ensure a complete understanding of the designs. - Experience in creating process blueprints and establishing business process requirements to drive out application requirements and metrics. Additional Information: - The candidate should have a minimum of 12 years of experience in Microsoft Dynamics 365 ERP Technical. - The ideal candidate will possess a strong educational background in business, technology, or a related field, along with a proven track record of delivering impactful solutions.

Role & responsibilities 15-20 years of experience in software architecture and development Deep expertise in Microsoft stack (C#, .NET Core, SQL Server, Azure) Have experience in front-end architecture designing. Sound knowledge in React or Angular. Strong understanding of Azure cloud (IaaS & PaaS), networking, and security Hands-on ability to troubleshoot, debug, and optimize applications Experience conducting code, architecture, and database reviews Strong mentorship skills to coach engineers across onshore/offshore teams Proficiency in CI/CD, test automation, and DevOps practices Experience in scaling and optimizing enterprise applications Ability to create PoCs and working code snippets for critical solutions Expected involvement & Deliverables : Technical Assessments & Reviews Code, architecture, database, log, and network assessments. Recommendations for improving performance, security, and maintainability. Proof-of-Concepts & Code Snippets Development of PoCs to validate architectural changes. Sample implementations for critical technical challenges. Development Best Practices & Team Enablement Define and promote CI/CD pipelines, test automation, and agile processes. Coaching for senior and mid-level engineers on best coding practices. Cloud & Infrastructure Optimization Review and improve Azure deployments (both IaaS and PaaS). Optimize cloud resource utilization and scalability. Roadmap & Strategic Planning Capacity planning and architecture roadmaps for flagship applications. Future tech adoption recommendations. We are looking only immediate joiners or serving notice period if you are interested kindly share updated resume in this mail id arpit.jain@mounttalent.com

- Lead the architectural design and implementation of scalable, reliable, and high-performance software systems for AI, AI Compiler and edge computing applications. - Collaborate with product managers, software engineers, and hardware engineers to ensure alignment of technical decisions with business objectives. - Define and maintain architectural best practices, guidelines, and documentation for the software engineering team. - Evaluate and recommend technologies, frameworks, and tools to optimize the performance and scalability of our solutions. - Ensure that all software architecture aligns with security, performance, and reliability standards. - Mentor and provide technical leadership to the engineering team, fostering a culture of collaboration and innovation. - Participate in code reviews, design discussions, and technical roadmap planning to ensure high-quality delivery. - Drive continuous improvement in system architecture and development processes to support the company's growth and evolving requirements. Necessary qualifications : - 8+ years of experience in software architecture, system design, and development of scalable, distributed systems. - Proven experience in designing edge-based solutions, compilers, runtime, firmware. - Strong programming skills in modern languages such as Python, C++ or similar language. - Expertise in designing high-performance, low-latency systems for AI/ML workloads. - Strong understanding of software development methodologies, DevOps practices, and CI/CD pipelines. - Familiarity with hardware-software co-design, embedded systems, and edge computing solutions is a plus. - Excellent problem-solving and communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.

We are seeking a highly skilled and experienced ServiceMax Technical Architect with over 15 years of experience in architecting and implementing ServiceMax solutions. The ideal candidate will have a strong background in technical architecture, design, and development of enterprise applications within the ServiceMax ecosystem. Key Responsibilities Lead the technical design and architecture of ServiceMax implementations. Collaborate with stakeholders to gather requirements and translate them into technical specifications. Utilize best practices to ensure high performance and scalability of ServiceMax applications. Provide technical guidance and mentorship to development teams. Conduct code reviews and ensure adherence to coding standards. Stay updated with the latest ServiceMax releases and features to leverage them effectively. Support project management in estimating development efforts and timelines. Participate in troubleshooting and resolving technical issues during and after implementations. Qualifications 15+ years of experience in software development and architecture. Proven experience with ServiceMax and its integration with other systems. Strong understanding of cloud technologies and architectures. Experience with Agile methodologies and project management. Excellent problem-solving skills and attention to detail. Strong communication and interpersonal skills. Education Bachelor s degree in Computer Science, Information Technology, or related field. Why Join Us Be part of a dynamic team that is dedicated to delivering innovative solutions. We offer competitive salaries, comprehensive benefits, and opportunities for professional growth.

Role Overview : We are seeking a highly experienced Sr. Salesforce CPQ Architect to lead solution design and implementation for complex Salesforce CPQ (Configure, Price, Quote) projects. The ideal candidate will collaborate with stakeholders to translate business requirements into scalable and robust CPQ architecture and ensure successful delivery within the Salesforce ecosystem. Key Responsibilities : - Architect end-to-end Salesforce CPQ solutions, including product configuration, pricing, discounting, and quoting processes. - Lead discovery sessions, gather business requirements, and convert them into technical solutions. - Design scalable, maintainable architecture following Salesforce and CPQ best practices. - Integrate CPQ with Sales Cloud, Billing, and third-party systems. - Provide technical leadership to the development team and ensure high-quality delivery. - Perform code reviews, ensure data integrity, and troubleshoot technical issues. - Maintain clear and complete technical documentation. - Collaborate with cross-functional teams including sales, operations, and finance. Required Skills & Experience : - 8+ years of Salesforce experience, with 4+ years specific to Salesforce CPQ. - Strong expertise in Salesforce CPQ architecture, configuration, and administration. - Experience with Revenue Cloud, Advanced Approvals, CPQ Discount Schedules, Product Rules, Price Rules. - Proficiency in Apex, Visualforce, LWC, and Salesforce automation tools (Flows, Process Builder). - Experience in integration design using REST/SOAP APIs. - Salesforce CPQ Certification is highly preferred. - Strong communication, leadership, and documentation skills. Work Hours : - Must be available to work in US Time Zone: 7:30 PM to 3:30 AM IST (Night Shift). Nice to Have : - Exposure to Salesforce Billing or other revenue management tools. - Familiarity with Agile/Scrum methodologies. - Experience working in a global team environment

Job Title: Salesforce Technical Architect Job Type: Full-Time Experience Required: 10+ Years Job Summary: We are looking for a seasoned and highly skilled Salesforce Technical Architect to lead the design and implementation of scalable, high-performance Salesforce solutions. This role requires a deep understanding of Salesforces platform capabilities, architecture best practices, and integration strategies across a wide range of industry use cases. You will drive architecture decisions, ensure technical excellence, and guide development teams through the full project lifecycle. Key Responsibilities: Lead the end-to-end design and architecture of complex Salesforce solutions across multiple clouds—including Automotive Cloud, Consumer Goods Cloud, Sales Cloud, Service Cloud, Experience Cloud, and custom applications. Establish and enforce architectural standards, development guardrails, and best practices to ensure scalability, performance, and maintainability. Collaborate with stakeholders, project managers, and technical teams to gather requirements and translate business needs into robust technical solutions. Architect and implement scalable data models, secure access frameworks, API integrations, and automation logic. Provide hands-on technical leadership to developers, ensuring adherence to best practices in coding, testing, and deployment. Conduct code and design reviews, and serve as the go-to expert for technical decision-making. Oversee CI/CD pipelines and release strategies using tools like Gearset , Copado , or Jenkins . Stay current with Salesforce releases, features, and innovations; proactively recommend relevant platform upgrades or enhancements. Ensure compliance with enterprise standards related to security, scalability, and performance. Mentor and support the professional development of junior architects and developers. Contribute to organizational knowledge through documentation, technical workshops, and internal forums. Required Qualifications: 10+ years of experience in enterprise software development, with at least 5 years in Salesforce development and architecture. Proven expertise in architecting and delivering Salesforce-based solutions in large, complex environments. Deep technical knowledge of Apex , Lightning Components , Visualforce , SOQL , and declarative configuration. Strong experience with integration tools and patterns (e.g., MuleSoft , Dell Boomi , REST/SOAP APIs ). Proficiency with Salesforce DevOps tools and CI/CD practices. In-depth understanding of data security, authentication (SSO, OAuth), and governance standards. Salesforce certifications including Platform Developer I & II , Application Architect , System Architect , or equivalent are required. CTA certification is highly preferred—or must be actively working towards achieving it. Excellent verbal and written communication skills; strong stakeholder and team collaboration capabilities. Experience working in Agile/Scrum delivery environments. Preferred Qualifications: Experience working across multi-cloud Salesforce environments. Domain knowledge in industries such as Financial Services , Healthcare , or Retail . Previous consulting or client-facing experience is highly desirable.

About the Role: We are looking for an SAP Technical Architect with 8+ years of experience in SAP Basis administration, across various SAP modules such as ECC, S/4HANA, BW/4HANA, etc. Requirements: Proven experience with SAP BTP services, including SAP Integration Suite, SAP HANA Cloud and SAP Launchpad. Strong understanding of SAP architecture, cloud deployment models such as AWS/Azure/GCP and system landscapes. Hands-on experience in SAP migrations (on-premises to cloud), end to end implementation and SAP upgrade projects. Expertise in troubleshooting technical issues and managing system performance. Familiarity with DevOps practices, CI/CD pipelines and automation tools in SAP landscapes is a plus. Relevant SAP certifications in Basis or BTP is an advantage. #LI-Onsite #LI-BL2

Warm Greetings from SP Staffing Services Private Limited!! We have an urgent opening with our CMMI Level 5 client for the below position. Please send your update profile if you are interested. Relevant Experience: 8 - 24 Yrs Location- Pan India Job Description : - Candidates should have minimum 2 Years hands on experience as Azure databricks Architect If interested please forward your updated resume to sankarspstaffings@gmail.com / Sankar@spstaffing.in With Regards, Sankar G Sr. Executive - IT Recruitment

Warm Greetings from SP Staffing Services Private Limited!! We have an urgent opening with our CMMI Level 5 client for the below position. Please send your update profile if you are interested. Relevant Experience: 8 - 24 Yrs Location- Pan India Job Description : - The Data Modeler will be responsible for the design, development, and maintenance of data models and standards for Enterprise data platforms. Build dimensional data models applying best practices and providing business insights. Build data warehouse & data marts (on Cloud) while performing data profiling and quality analysis. Identify business needs and translate business requirements to Conceptual, Logical, Physical and semantic, multi-dimensional (star, snowflake), normalized/denormalized, Data Vault2.0 model for the project. Knowledge of snowflake and dbt is added advantage. Create and maintain the Source to Target Data Mapping document for this project. Includes documentation of all entities, attributes, data relationships, primary and foreign key structures, allowed values, codes, business rules, glossary terms, etc. Develop best practices for standard naming conventions and coding practices to ensure consistency of data models. Gather and Publish Data Dictionaries: Maintain data models and capture data models from existing databases and record descriptive information. Work with the Development team to implement data strategies, build data flows and develop conceptual data models. Create logical and physical data models using best practices to ensure high data quality and reduced redundancy. Optimize and update logical and physical data models to support new and existing projects. Data profiling, business domain modeling, logical data modeling, physical dimensional data modeling and design. Data design and performance optimization for large Data Warehouse solutions. understanding data - profile and analysis (metadata (formats, definitions, valid values, boundaries), relationship/usage) Create relational and dimensional structures for large (multi-terabyte) operational, analytical, warehouse and BI systems. Should be good in verbal and written communication. If interested please forward your updated resume to sankarspstaffings@gmail.com / Sankar@spstaffing.in With Regards, Sankar G Sr. Executive - IT Recruitment