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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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Skills & Qualifications
- 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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