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Job Description & How to Apply Below
Sr. Data Engineer (Full Stack)
Primary skills: Microsoft Fabric, Power BI (Semantic Modelling), Python/SQL, AI Integration, Azure Dev Ops (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 Dev Ops (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 Dev Ops (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.
Position Requirements
10+ Years
work experience
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