Job Purpose To design and deliver AI-powered Business Intelligence solutions by integrating Databricks Genie, PowerBI Co-Pilot & Semantic Models, and Metric Views on top of a robust end-to-end data engineering stack.

The role focuses on enabling self-service analytics using natural language (GenAI), ensuring business-friendly data consumption, and building governed, scalable, and high-performance data ecosystems across batch and real-time pipelines.Duties and Responsibilities

- Translate business problems into AI-driven BI solutions
- Own end-to-end delivery: ingestion ? transformation ? semantic layer ? AI consumption
- Design scalable data architecture aligned with lakehouse principles
- Ensure data quality, governance, and metric consistency
- Collaborate with business teams to onboard them onto Genie-based analytics
- Optimize performance of queries, pipelines, and AI responses
- Establish best practices for AI in BI (prompting, semantic tuning, governance)
- Drive adoption of self-service BI with minimal dependency on tech teamsKey Decisions / Dimensions
- Define semantic layer design and metric definitions
- Decide GenAI prompting strategies and instruction frameworks
- Prioritize data vs AI optimization trade-offs
- Handle production issues with RCA and long-term fixes
- Drive architectural decisions for lakehouse + AI integrationMajor Challenges




- Ensuring accuracy and trust in AI-generated insights
- Driving adoption of GenAI-based BI over traditional dashboards
- Maintaining semantic consistency across multiple tools
- Balancing performance, cost, and scalability
- Managing dependencies across data engineering, AI, and business teamsRequired Qualifications and Experience
- Azure Databricks – PySpark, SQL, Delta Lake
- PowerBI – CoPilot, Semantic Model
- Strong experience in Semantic Modeling & Metrics Layer design
- Hands-on with Databricks Genie / GenAI-based BI workflows
- Databricks One (Unified BI Experience)
- Prompt Engineering / Instruction tuning for AI systems
- Python (Pandas, PySpark, FastAPI)
- Azure Data Factory (ADF) for ETL pipelines
- Robust SQL and data modeling skills

Good to Have

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

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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, PowerBI CoPilot

3 Semantic Layer Semantic Models, Metric Views

4 ETL & Orchestration Azure Data Factory

5 Programming Python, C#/.NET

6 Cloud Platform Azure (Preferred)

7 DevOps CI/CD Pipelines, Git

📌 Senior Data Engineer (Pune)
🏢 Bajaj Finance
📍 Pune