Microsoft Fabric SME

Role Summary 

Avanade India’s Intelligence Data Platforms practice is looking for a Microsoft Fabric SME to be a deep technical specialist on modern data estate, data lake, data warehouse, and data migration projects built on Microsoft Fabric. This is a hands-on, individual-contributor role for someone who wants to own the technical build — designing and implementing data pipelines and platform components, solving complex implementation challenges, and providing specialist guidance to the wider delivery team. 

Key Responsibilities 

• Design and build components of Microsoft Fabric solutions: OneLake, Lakehouse/Warehouse, Data Factory (Fabric) pipelines/dataflows, Real-Time Intelligence, and Power BI-based semantic and reporting layers. 

• Implement data ingestion, transformation, and modeling patterns for modern data estate builds — data lake, data warehouse, and lakehouse architectures. 

• Act as the technical specialist/go-to resource on Microsoft Fabric within project teams, resolving complex implementation issues and edge cases. 

• Execute data migration workstreams — moving data and workloads from legacy platforms (on-prem warehouses, Synapse, Databricks, Snowflake, or other cloud data platforms) to Fabric. 

• Support the Fabric Architect/Lead in solution design, technical estimation, and implementation planning. 

• Write and review production-quality pipeline code and configurations; ensure adherence to engineering best practices, testing, and CI/CD standards. 

• Apply data governance and security practices during build — Purview integration, Fabric workspace governance, and data lineage. 

• Support post-go-live stabilization and production issue troubleshooting for deployed data solutions. 

• Guide junior data engineers on Microsoft Fabric implementation patterns and best practices, without formal team-lead accountability. 

• Contribute to reusable pipeline assets, accelerators, and technical documentation for the Data Engineering job family. 

• Stay current with the Fabric roadmap and broader Microsoft data platform ecosystem, evaluating new capabilities for project use. 

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• 8–12 years in data engineering roles, with strong recent hands-on experience building solutions on Microsoft Fabric. 

• Hands-on experience with Microsoft Fabric: OneLake, Lakehouse, Data Warehouse, Data Factory pipelines/dataflows, Notebooks (Spark), and Power BI integration. 

• Strong background in modern data estate patterns — data lake and data warehouse architecture (medallion architecture, dimensional modeling). 

• Hands-on experience executing data migration workstreams — legacy on-prem or cloud platforms to Fabric (or migrations into Synapse/Databricks with a clear path to Fabric). 

• Familiarity with the broader Azure data ecosystem: Azure Synapse Analytics, Azure Data Factory, Azure Databricks, ADLS Gen2, Azure SQL. 

• Strong SQL, data modeling, and performance tuning skills; working knowledge of Spark/PySpark. 

• Working knowledge of data governance and security practices — Microsoft Purview, role-based access, data lineage. 

• Comfortable working directly with technical leads/architects and client technical teams during delivery. 

Preferred / Good to Have 

• Microsoft certifications: Fabric Analytics Engineer Associate (DP-600), Azure Data Engineer Associate (DP-203/DP-700). 

• Exposure to AI/ML integration on Fabric (Fabric Data Science, Copilot in Fabric) or broader GenAI/agentic data use cases. 

• Exposure to CI/CD and DevOps practices for data platforms (Azure DevOps, GitHub Actions). 

• Experience working across multiple industry domains (manufacturing, BFSI, consumer goods, energy, healthcare, or others). 

• Experience working in a global delivery / SI environment with distributed teams across geographies

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