Microsoft Fabric Architect

Job description

Role Summary Avanade India’s Data & AI practice is looking for a Microsoft Fabric Architect to drive presales solutioning and technical architecture for modern data estate, data lake, data warehouse, and data migration engagements built on Microsoft Fabric, stepping into delivery leadership as engagements require. This is a client-facing role for someone who enjoys shaping opportunities as much as solving hard architecture problems — from client workshops and proposal-stage solutioning through to guiding implementation teams when needed. Key Responsibilities Lead presales solutioning for Microsoft Fabric opportunities — architecture proposals, effort estimation, solution demos, and client workshops — partnering with account and practice leadership on pursuits. Design end-to-end Microsoft Fabric solution architectures, including OneLake , Lakehouse/Warehouse, Data Factory (Fabric), Real-Time Intelligence, and Power BI-based semantic and reporting layers. Define data platform strategy, target-state architecture, and migration roadmaps in collaboration with client stakeholders. Architect modern data estate builds — data lake, data warehouse, and lakehouse patterns — including migrations from legacy platforms (on-prem warehouses, Synapse, Databricks, Snowflake, or other cloud data platforms) to Fabric. Step into delivery as needed to provide technical leadership on active engagements: solution design, architecture governance, design reviews, performance and cost optimization, and production readiness. Establish data architecture standards, security/governance models (Purview, Fabric workspace governance, data lineage), and CI/CD practices for Fabric-based delivery. Act as a trusted technical advisor to client stakeholders, translating business requirements into scalable, well-governed data architectures. Mentor data engineers and architects on project teams; contribute to reusable accelerators and IP for the practice. Stay current with the Fabric roadmap and broader Microsoft data platform ecosystem, bringing new capabilities into client proposals and solutions. . Required Skills & Experience 12–15 years in data engineering/architecture roles, with the most recent chapter as a Data Architect actively implementing Microsoft Fabric-based solutions. Hands-on architecture experience with Microsoft Fabric: OneLake , Lakehouse, Data Warehouse, Data Factory pipelines/dataflows, Notebooks (Spark), and Power BI integration. Strong background in modern data estate design — data lake and data warehouse architecture patterns (medallion architecture, dimensional modeling, data mesh concepts where applicable). Proven experience leading data migration programs — legacy on-prem or cloud platforms to Fabric (or migrations into Synapse/Databricks with a clear path to Fabric). Solid grounding in the broader Azure data ecosystem: Azure Synapse Analytics, Azure Data Factory, Azure Databricks, ADLS Gen2, Azure SQL — with the ability to compare and position Fabric against these. Strong SQL, data modeling, and performance tuning skills; working knowledge of Spark/ PySpark . Experience with data governance and security frameworks — Microsoft Purview, role-based access, data lineage, and compliance considerations in enterprise environments. Demonstrated experience in presales solutioning — proposals, estimation, and client-facing workshops — alongside hands-on delivery capability. Experience mentoring teams and owning technical delivery quality on medium-to-large engagements. Preferred / Good to Have Microsoft certifications: Fabric Analytics Engineer Associate (DP-600), Azure Data Engineer Associate (DP-203/DP-700), Azure Solutions Architect Expert. Exposure to AI/ML integration on Fabric (Fabric Data Science, Copilot in Fabric) or broader GenAI/agentic data use cases. 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. Prior experience contributing to reusable accelerators, frameworks, or practice-building initiatives. .