Job Summary

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

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 current 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 / 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 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 Experience Must Have
Azure Databricks - PySpark, SQL, Delta Lake
Semantic Modeling & Metrics Layer design
Hands-on with Databricks workflows
Pyspark (Pandas, PySpark, FastAPI)
Azure Data Factory (ADF) for ETL pipelines
Robust SQL and data modeling skills

Valuable to Have
Cosmos DB / MongoDB (NoSQL concepts)
Azure Data Explorer (KQL)

Data Stack (Mandatory for Screening)
Databricks Lakehouse - PySpark, SQL, Delta Lake
AI for BI - Databricks Genie, Genie Rooms, Instructions, Agents
ETL & Orchestration - Azure Data Factory
Programming - PySpark
Cloud Platform - Azure (Preferred)
DevOps - CI/CD Pipelines, Git

📌 Data Engineer Pune
🏢 Bajaj Finance
📍 Pune