Lead Data Platform Engineer

Job Title : Sr. Data Engineer (Full Stack)

Primary skills: Microsoft Fabric, Power BI (Semantic Modelling), Python/SQL, AI Integration, Azure DevOps (CI/CD).

Mode of work : Hybrid (3 days in office)

Experience : 8–10+ Yrs.

L ocation : HYD

Responsibilities

• End-to-End Data Engineering: Design, develop, and maintain scalable ELT/ETL pipelines and lakehouse structures within Microsoft Fabric.
• Full Stack Analytics: Model and publish curated, analysis-ready datasets and semantic models in Power BI that illuminate key insurance metrics.
• AI & Innovation: Proactively produce automated analytic solutions and integrate AI/ML capabilities into data products to drive business value.
• Stakeholder Collaboration: Partner directly with business leaders (Underwriting, Claims, Finance) to translate complex questions into documented requirements and actionable data solutions.
• Technical Standards: Follow platform standards, optimizing for performance, reliability, and cost-efficiency within the Azure/Fabric ecosystem.
• Governance & Quality: Follow and implement documentation standards, governance, and data quality controls across all datasets.
• CI/CD Excellence: Use Azure DevOps (ADO) for version control (branching, pull requests) and release pipelines to harden delivery and improve repeatability.
• Architecture Documentation: Document technical architecture and workflows with clear diagrams and runbooks to reduce operational risk.

Requirements

• 8–10 years of experience in data engineering, specifically within the P&C Insurance space.
• Deep Proficiency in Microsoft Fabric (highly required).
• Expertise in Power BI (developing complex semantic models and intuitive dashboards).
• Advanced SQL and Python skills for data manipulation and AI integration.
• Proven experience with Azure DevOps (ADO) and modern CI/CD practices.
• Experience with cloud platforms, primarily Azure.
• Strong analytical and problem-solving skills with the ability to translate business needs into technical products.

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