Explicitly requires vibe coding and AI-assisted development (Windsurf, Codex, GitHub Copilot, Cursor) and building agentic solutions.
About the Role
Senior Data Management Engineer (Vice President) in Pune responsible for designing and implementing scalable ETL/ELT data pipelines, integrating AI-assisted development and agentic solutions, and maintaining CI/CD and automated testing for the Finance Platform's Client Profitability Engineering team.
Job Description
Role
Vice President, Data Management Engineer on the Finance Platform’s Client Profitability Engineering team based in Pune. The role focuses on translating business requirements into scalable ETL/ELT models, building and maintaining data pipelines and CI/CD processes, integrating AI-assisted development techniques and agentic solutions, and supporting ongoing operations and improvements.
Key Responsibilities
- Translate business requirements into ETL/ELT logical models designed for scalability and flexibility.
- Design, develop, and implement robust data pipelines using Spark.
- Define and deliver reusable components within the ETL/ELT framework and establish optimal data flows for integration and migration.
- Integrate emerging data management technologies and software engineering tools; apply security and privacy principles.
- Design, construct, and maintain CI/CD pipelines across multiple integration and test environments.
- Install, configure, and manage automated testing tools within the environment.
- Utilize AI-based development/vibe coding tools and techniques (e.g., Windsurf, Codex) to develop solutions and accelerate development workflows.
- Build and work with agentic solutions and participate in deployment processes following change controls.
- Provide maintenance, support, enhancements, and continuous improvement recommendations for existing systems and platforms.
- Collaborate cross-functionally with full-stack engineers, business users, project managers and other engineers, and share team responsibility for commitments.
Requirements / Qualifications
- Proven experience designing, developing, and implementing large-scale projects in financial services using Data Warehousing and ETL tools (including Spark).
- Proficient creating ETL transformations and jobs with Spark and automating workflows with orchestration tools such as Airflow and Control-M.
- Strong hands-on knowledge of SQL, Python, Java, and reporting tools like Power BI.
- Experience with relational databases such as Oracle, Snowflake, SQL Server or similar.
- Familiarity with Big Data and distributed frameworks: Spark, Kubernetes, Hadoop, Hive.
- Experience designing, testing and managing APIs for inter-process communication.
- Experience building agents and agentic solutions; familiarity with AI-first development practices.
- Experience using AI-assisted developer tools (e.g., GitHub Copilot, Cursor, Windsurf, Codex) for code generation, debugging, tests and documentation.
- Comprehensive experience building and managing CI/CD pipelines and automated testing.
- Basic understanding of Azure cloud components.
- Knowledge of monitoring tools such as AppDynamics, Splunk, and Moogsoft.
- Strong problem-solving skills, commitment to best practices in design/development/testing/release management, and customer service orientation.
Location
Skills
Data Modeling ETL/ELT System Design CI/CD Automation Testing Deployment Monitoring Security and Privacy API Design Cross-functional Collaboration Problem Solving Documentation Customer Service Self-motivation