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 teams
Key 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 integration
Major 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 teams
Required 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
• Strong SQL and data modeling skills
Valuable 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 (India)
🏢 Bajaj Finance
📍 India