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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