Microsoft Fabric -Data Engineer

About the Job Experience: 7 -9 years Work Location: Bangalore/Hyderabad Designation: Module lead (Microsoft Fabric Data engineer) Role Description: We are looking for a Senior Data Engineer with strong Microsoft Fabric and Python skills to build and deliver production-grade data pipelines for a specialty medical stop loss insurance enterprise's claims modernization platform. You will own end-to-end pipeline development across assigned workstreams — ingestion, transformation, data quality, and Gold layer views — working as part of a focused delivery team under direct Technical Lead guidance. This is a build role: you write code, ship pipelines, and own the quality of your workstream output. 5–8 years Tagline/Tech Stack Snapshot - Microsoft Fabric Pipelines | Medallion Architecture | Data Quality Engineering | Claims Data Modernization Key/Core Responsibilities/What you’ll do: • 5+ years in data engineering with hands-on experience building and maintaining production-grade data pipelines • Practical, production-level experience in Microsoft Fabric — Fabric Data Factory pipelines, OneLake Lakehouses, and Delta Lake patterns (not just learning-lab exposure) • Expert Python and SQL — you write complex transformation logic, debug data issues independently, and review your own code before submitting for review • Experience building data quality validation: schema validation, reconciliation, record-level checks, and exception/quarantine workflows • Solid understanding of medallion (Bronze / Silver / Gold) architecture — you have built at least one layer end-to-end in a real project • Familiarity with Azure AI Services — Azure Document Intelligence or similar for extracting structured data from documents or semi-structured files • Comfortable working in an Agile delivery cadence with Technical Lead direction and cross-timezone collaboration Qualifications Bachelor’s degree in computer science or equivalent experience in leading development teams.

Must have skills Microsoft Fabric, Matillion, Python, SQL, , Azure Databricks, Delta Lake, Medallion Architecture, Azure AI Services, Microsoft Fabric Pipelines Required Skills Ingestion Pipeline Development • Build Fabric Data Factory pipelines for batch file intake from assigned Phase 1 TPAs — handling xlsx, csv, and txt files across varying source channels (email, FTP, secure portal) • Implement schema registry alias mappings for your assigned TPA file variants — handling known format differences and flagging schema drift for Technical Lead review Medallion Transformations — Bronze, Silver & Gold • Implement Bronze layer Delta Lake tables with immutable append-only transaction history and correct partition and retention configurations • Build Silver layer transformations per the canonical data model — code standardization (diagnosis, procedure, revenue), member/subscriber normalization, and adjustment/void/reversal handling in PySpark/SQL Data Quality & Exception Handling • Implement DQ rule sets for assigned TPA workstreams — record-level validation, cross-field checks, and business rule enforcement using WinAIDM Data Quality Agent • Build exception triage outputs: structured failure reason codes, quarantine routing, and failed record logging integrated with the review queue UI backend Historical Data Migration • Participate in the historical migration pilot for assigned TPAs — apply current-state pipeline patterns to 7+ years of historical data and document data quality findings • Execute Bronze archival or full reprocessing path per the go/no-go decision; ensure historical records are correctly partitioned and labeled in the lakehouse Collaboration & Standards • Participate in daily standups, sprint planning, and code reviews — contributing to and receiving feedback from the Technical Lead • Follow WinWire's WinAIDM accelerator standards for pipeline development: using AI- assisted ingestion, quality, and transformation agents for consistent implementation patterns • Azure Databricks / PySpark experience for large-scale data transformation or historical migration workloads • Power BI or Fabric semantic model experience — useful for understanding Gold layer consumer requirements and validating view outputs • Exposure to healthcare or insurance claims data (837, 835 formats, TPA file structures, eligibility concepts) • Microsoft Fabric Analytics Engineer (DP-600) or Azure Data Engineer Associate (DP-203) certification