Senior Data Engineer

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.

•  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

Good 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, 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