Microsoft Fabric Data Engineer

Job Overview: We are looking for a Senior Microsoft Fabric Data Engineer to serve as a technical anchor and architect for enterprise-scale analytics platforms. This role is responsible for designing end-to-end modernization pathways -helping clients transition seamlessly from legacy warehouses (or platforms like Databricks/Snowflake/Synapse) into a unified Microsoft Fabric ecosystem. You will own platform topology, establish enterprise governance, optimize Fabric capacities, and mentor a pod of engineers to deliver scalable, secure, and AI-ready data footprints. Key Responsibilities: Solution Architecture: Architect end-to-end data landscapes using the full Fabric stack: OneLake, Lakehouses, Warehouses, Data Factory, Notebooks, and Real-Time Intelligence (Eventstreams/KQL). Proven experience implementing Medallion Architectures and managing unstructured, semi-structured, and structured data footprints. Platform Governance & Topology: Define tenant-level workspace strategy, Hub-and-Spoke integration patterns, and domain boundaries. Implement data governance, lineage tracking, and classifications via Microsoft Purview. Performance Reliability & Cost Tuning: Manage and optimize Microsoft Fabric platform performance. Monitor capacity utilization (F-SKUs), optimize query workloads, manage Delta table maintenance (OPTIMIZE / VACUUM), and enforce V-Order/Z-Order sorting to ensure cost-effective operations. Enterprise BI & Data Trust: Design robust Power BI semantic models utilizing Direct Lake mode to enable real-time reporting without data duplication. Centralize complex, production-grade DAX business logic. DevOps & Release Management: Establish CI/CD frameworks and environment strategy using Fabric Git integration and Azure DevOps/GitHub release management. AI & Advanced Analytics Support: Design data pipelines structured to feed downstream machine learning models and modern AI workloads (such as vector databases, semantic search, and RAG frameworks). Technical Leadership: Mentor junior engineers through design/code reviews, establish reusable engineering frameworks, and assist leadership with effort estimations or Proof-of-Concepts (PoCs). Technical Requirements: Proven Experience: 6+ years in Data Engineering/Architecture, with 1–2 years of dedicated, hands-on production experience in Microsoft Fabric. Performance Tuning Expert: Deep understanding of the VertiPaq engine, DAX optimization, and Fabric capacity management (managing compute load across F-SKUs). Spark & Delta Lake Expert: Advanced mastery of PySpark, Spark SQL, and optimization techniques for Delta Lake. Expert SQL & Integration: Expert-level SQL script writing alongside deep knowledge of REST APIs, data mirroring, and shortcuts for cross-platform data blending. Security & Compliance: Practical experience building Row-Level Security (RLS) and Object-Level Security (OLS) frameworks across data and reporting boundaries. Preferred Certifications: Microsoft DP-600 (Fabric Analytics Engineer Associate) or DP-700 (Microsoft Fabric Data Engineer Associate) is highly preferred.