Job Purpose To effectively design, develop, and manage data solutions using ETL technologies such as Azure Databricks (ADB), Azure Data Factory (ADF), and SQL.

Duties and ResponsibilitiesKEY RESPONSIBILITIES

- Translate business requirements into technical solutions in collaboration with the PMO team.
- Own end-to-end delivery of data projects, ensuring on-time execution and adherence to quality standards.
- Design technical architecture and guide development efforts for enhancements and new projects.
- Develop and maintain robust ETL pipelines and data integration modules across systems.
- Ensure high data quality, data anomaly resolution of critical process issues.
- Monitor and resolve performance bottlenecks in data workflows and programs.
- Establish best practices, standard operating procedures, and drive their implementation across teams.
- Act as a liaison with business users and product managers to support daily data needs and strategic initiatives.
- Coordinate with internal and external development teams to troubleshoot and resolve issues efficiently.
- Manage workload through effective planning, prioritization, and progress tracking.

Key Decisions / DimensionsKEY DECISIONS / DIMENSIONS

- Define semantic layer design and metric definitions.
- Prioritize data vs AI optimization trade-offs.
- Handle production issues with RCA and long-term fixes.
- Drive architectural decisions for lakehouse Data integration.

Major ChallengesMAJOR CHALLENGES





- Ensuring Data Delivery within TAT.
- Driving adoption of GenAI-based BI over traditional dashboards.
- Balancing performance, cost, and scalability.
- Managing dependencies across data engineering, AI, and business teams.

Required Qualifications and ExperienceREQUIRED SKILLS & EXPERIENCEMust Have

- Azure Databricks - PySpark, SQL, Delta Lake.
- Strong experience in Semantic Modeling & Metrics Layer design.
- Hands-on with Databricks workflows.
- Pyspark (Pandas, PySpark, FastAPI).
- Azure Data Factory (ADF) for ETL pipelines.
- Strong SQL and data modeling skills.

Positive to Have

- Cosmos DB / MongoDB (NoSQL concepts).
- Azure Data Explorer (KQL).

DATA STACK (MANDATORY FOR SCREENING) | SNo | Data Platform / Concepts | Associated Technologies | |-----|--------------------------|---------------------------------------------| | 1 | Databricks Lakehouse | PySpark, SQL, Delta Lake | | 2 | AI for BI | Databricks Genie, Genie Rooms, Instructions, Agents | | 4 | ETL & Orchestration | Azure Data Factory | | 5 | Programming | Pyspark | | 6 | Cloud Platform | Azure (Preferred) | | 10 | DevOps | CI/CD Pipelines, Git |

LocationsBASIC SECTION

- Job Level: GB03
- Job Title: Data Engineer - IT, Data Technologies, Data Technology - Delivery
- Job Location Country: India
- State: MAHARASHTRA
- Region: West
- City: Pune
- Location Name: Pune Corporate Office - Mantri Tier Megapolis

📌 Data Engineer (India)
🏢 Bajaj FinServ
📍 India