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AI technologies (such as Spark, Kafka, Databricks, and Snowflake), programming (including Java, Scala, Python, and SQL), API integration patterns (like HTTP/REST and GraphQL), and leading cloud platforms (Azure, AWS, GCP) to design and deliver data warehousing solutions.  <br/> </li></ul><p> <b>  Shift timing (if any): </b> 12:30 PM to 9:30 PM IST</p><p> <b>  Location / Additional Location (if any): </b> Bangalore, Hyderabad</p><p> <b>  Overall Experience: </b></p><ul> <li>  Typically requires a minimum 15 years of progressive experience in data engineering, data architecture, or related fields. </li> <li>  Demonstrated experience leading complex data projects, managing teams, and delivering end-to-end data solutions in large or matrixed organizations is highly valued. </li> <li>  Experience with cloud data platforms, big data technologies, and implementing best practices in data governance and DevOps is strongly preferred. </li></ul><p> <b>  Primary / Mandatory skills: </b></p><ul> <li>  <b>   Delivery:  </b>  Proven experience in managing and delivering complex data engineering and AI solutions for major business challenges. </li> <li>  <b>   Data Architecture &amp; Modeling:  </b>  <br/>  Expertise in designing scalable, high-performance data architectures (e.g., data warehouses, data lakes, data marts) and creating robust data models. </li> <li>  <b>   ETL/ELT Development:  </b>  <br/>  Advanced skills in building, optimizing, and maintaining data pipelines using modern ETL/ELT tools (e.g., Informatica, Talend, dbt, Azure Data Factory). </li> <li>  <b>   Cloud Platforms:  </b>  <br/>  Proficiency with cloud data services and platforms such as AWS, Azure, or Google Cloud (e.g., Redshift, Snowflake, Databricks, BigQuery). </li> <li>  <b>   Programming Languages:  </b>  <br/>  Strong coding ability in SQL and at least one general-purpose language (e.g., Python, Scala, Java). </li> <li>  <b>   Big Data Technologies:  </b>  <br/>  Experience with distributed data processing frameworks (e.g., Spark, Hadoop) and real-time streaming tools (e.g., Kafka). </li> <li>  <b>   Data Governance &amp; Quality:  </b>  <br/>  Knowledge of data governance practices, data lineage, data cataloging, and implementing data quality checks. </li> <li>  <b>   CI/CD &amp; Automation:  </b>  <br/>  Experience in automating data workflows, version control (e.g., Git), and deploying CI/CD pipelines for data applications. </li> <li>  <b>   Analytics &amp; AI/ML Integration:  </b>  <br/>  Ability to support advanced analytics and integrate machine learning pipelines with core data platforms. </li> <li>  <b>   Leadership &amp; Collaboration:  </b>  <br/>  Proven track record in leading teams, mentoring engineers, and collaborating with business, analytics, and IT stakeholders. </li> <li>  <b>   Problem Solving &amp; Communication:  </b>  <br/>  Strong analytical, troubleshooting, and communication skills to translate business needs into technical solutions. </li></ul><p></p><p> <b>  Secondary / Desired skills: </b></p><ul> <li>  <b>   Data Visualization:  </b>  <br/>  Experience with BI tools such as Power BI, Tableau, or Looker for creating dashboards and visual analytics. </li> <li>  <b>   AI/ML Model Operationalization:  </b>  <br/>  Familiarity with deploying, monitoring, and scaling machine learning models in production environments (MLOps). </li> <li>  <b>   API &amp; Microservices Development:  </b>  <br/>  Understanding of building and consuming RESTful APIs and microservices for data integration. </li> <li>  <b>   Data Security &amp; Privacy:  </b>  <br/>  Knowledge of data encryption, access controls, and compliance with data privacy regulations (GDPR, CCPA, SOX). </li> <li>  <b>   Data Catalogs &amp; Metadata Management:  </b>  <br/>  Experience with tools like Alation, Collibra, or Azure Purview for cataloging and managing metadata. </li> <li>  <b>   Workflow Orchestration:  </b>  <br/>  Hands-on with workflow tools (e.g., Apache Airflow, Control-M, Prefect) for scheduling and monitoring data jobs. </li> <li>  <b>   Performance Tuning:  </b>  <br/>  Skills in optimizing queries, storage, and processing for cost and speed. </li> <li>  <b>   Change/Data Release Management:  </b>  <br/>  Experience in managing data schema evolution, versioning, and deployment coordination. </li> <li>  <b>   GitHub &amp; Copilot Proficiency:  </b>  <br/>  Proficient in using GitHub for version control, collaboration, and CI/CD pipelines; experience leveraging GitHub Copilot to enhance coding efficiency and foster team productivity. </li> <li>  <b>   DevOps for Data:  </b>  <br/>  Exposure to infrastructure-as-code (Terraform, CloudFormation) and containerization (Docker, Kubernetes) for data workloads. </li> <li>  <b>   Domain Knowledge:  </b>  <br/>  Understanding of Finance, Telecom, Retail, or the relevant business domain to better align data solutions with business needs. </li> <li>  <b>   Project Management:  </b>  <br/>  Familiarity with Agile, Scrum, or Kanban methodologies for managing data projects. </li> <li>  <b>   Stakeholder Management:  </b>  <br/>  Ability to effectively engage with non-technical users, translate requirements, and manage expectations. </li></ul><p></p><p></p><p> <b>  Additional information (if any): </b></p><ul> <li>  <b>   Leadership &amp; Mentorship:  </b>  <br/>  Expected to mentor and develop junior engineers, foster a culture of knowledge sharing, and lead by example in adopting best practices. </li> <li>  <b>   Cross-Functional Collaboration:  </b>  <br/>  Will work closely with data scientists, business analysts, product managers, and IT teams to deliver end-to-end solutions that meet business needs. </li> <li>  <b>   Innovation &amp; Continuous Improvement:  </b>  <br/>  Encouraged to stay current with emerging technologies and trends in data engineering, AI/ML, and cloud platforms, and to proactively recommend and implement improvements. </li> <li>  <b>   Ownership &amp; Accountability:  </b>  <br/>  Responsible for the entire data engineering lifecycle, including architecture, implementation, monitoring, and optimization. </li> <li>  <b>   Communication Skills:  </b>  <br/>  Must be able to translate complex technical concepts into clear, actionable insights for non-technical stakeholders and leadership. </li> <li>  <b>   Change Management:  </b>  <br/>  Experience managing change in fast-paced environments and guiding teams through technology transformations is highly valued. </li> <li>  <b>   Quality &amp; Compliance Focus:  </b>  <br/>  Commitment to data quality, security, and compliance is essential, with experience in implementing and maintaining controls and standards. </li> <li>  <b>   Business Impact:  </b>  <br/>  Expected to contribute to measurable business outcomes by enabling data-driven decision-making and supporting organizational goals. </li></ul><p> <b>  Certifications (if any specific): </b></p><ul> <li>  Cloud Platform Certifications (AWS, Azure, GCP) </li> <li>  Data Engineering &amp; 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