Lead/Senior Microsoft Fabric Data Engineer

Lead / Senior Microsoft Fabric Data Engineer

Location : Bangalore (On-site, with flexibility for 12 remote days)

Job Type : Permanent

Experience Level : 8+ years in data engineering overall, with 2+ years in a leadership/architect capacity

About the Role :

We are seeking an experienced Lead Microsoft Fabric Data Engineer to drive our initiative to modernize our legacy BI platform onto Microsoft Fabric. This is a hands-on technical leadership role : you will architect the core Fabric solution yourself, set practical engineering standards, and guide a small team through a phased migration. We expect most candidates to bring strong, deep Azure Synapse/ADF/Databricks experience plus 1.52+ years of practical, hands-on Microsoft Fabric work.

Key Responsibilities : 1. Technical Leadership & Hands-On Architecture :

• Own the end-to-end technical design of the Fabric Lakehouse/Warehouse solution, and remain hands-on in build for the first 2-3 quarters.

• Set pragmatic engineering standards and coding conventions for the Fabric platform (naming, folder structure, notebook/pipeline patterns).

• Act as the team's go-to person for Fabric - evaluate new features/capacity options and recommend what's actually useful for our workloads.

• Mentor 2-4 mid-level data engineers day to day on Fabric and Spark/SQL best practices.

2. Lakehouse & Warehouse Design :

• Design the Lakehouse/Data Warehouse architecture in Fabric, including medallion (Bronze/Silver/Gold) layout.

• Define workspace and domain structure, full enterprise data-mesh patterns are a plus, not a prerequisite.

• Right-size Fabric capacity (F-SKU) and monitor/optimize compute and storage cost.

• Choose sensibly between Direct Lake, Import, and Direct Query per use case.

3. Legacy Platform Migration :

• Assess our current BI/DW stack and produce a practical, phased migration plan.

• Lead pilot migrations of 1-2 priority workloads, validate the approach, then scale to the rest.

• Prior experience migrating any legacy platform (SQL Server, Synapse, Teradata, Oracle, Cognos, etc.) to a modern cloud/Fabric target is valued.

• Define simple, trackable success metrics for migration progress and data quality.

4. Core Data Engineering :

• Build and review data pipelines using Fabric Data Factory, Dataflows Gen2, and Notebooks (PySpark/Spark SQL).

• Implement incremental loads, CDC, and SCD patterns.

• Where relevant, build real-time ingestion with Event streams and KQL Database - deep Real-Time Intelligence expertise is a plus, not a must-have.