Senior Data Engineer

Responsibilities

• Design, build, and maintain enterprise-scale lakehouse architectures using Microsoft Fabric
• Architect end-to-end data engineering solutions on Azure, including ingestion, transformation, storage, and serving layers
• Build and optimize data pipelines using Fabric Data Factory, Dataflows, and Notebooks (Spark)
• Design and manage OneLake, Lakehouse, and Warehouse artifacts within Microsoft Fabric
• Develop scalable ETL/ELT pipelines integrating structured and unstructured data from diverse enterprise sources
• Implement data modeling best practices (dimensional modeling, medallion architecture — bronze/silver/gold layers)
• Collaborate with business and analytics teams across retail, financial services, FMCG, and utilities to understand domain-specific data needs
• Ensure data quality, governance, security, and compliance across the platform (row-level security, sensitivity labels, Purview integration)
• Optimize pipeline performance, cost, and reliability for large-scale enterprise datasets
• Partner with architects and stakeholders to define data platform strategy and roadmap
• Mentor junior data engineers and contribute to engineering best practices and standards
• Support migration of legacy data warehouse/ETL solutions to modern lakehouse architecture on Azure/Fabric

Requirements

• 7–10 years of experience in data engineering and analytics, with significant hands-on experience in Azure Data Engineering
• Strong, demonstrable expertise in Microsoft Fabric — Lakehouse, Data Factory, Dataflows Gen2, Notebooks, OneLake, Power BI integration
• Deep understanding of lakehouse architecture and medallion (bronze/silver/gold) design patterns
• Proficiency with Azure data services: Azure Data Factory, Azure Synapse Analytics, Azure Databricks, ADLS Gen2
• Strong SQL and Spark (PySpark/Scala) skills for large-scale data transformation
• Experience delivering enterprise-grade data solutions in one or more of: retail, financial services, FMCG, or utilities
• Solid understanding of data governance, security, and compliance frameworks (Microsoft Purview, RBAC, data masking)
• Experience with CI/CD for data pipelines (Azure DevOps, Git-based deployment)
• Strong grasp of data modeling techniques (star schema, slowly changing dimensions, etc.)
• Excellent stakeholder management and communication skills, with experience working directly with business and analytics teams
• Ability to translate ambiguous business requirements into scalable technical solutions

Nice to Have

• Microsoft certifications (e.g., DP-600 Fabric Analytics Engineer, DP-203 Azure Data Engineer)
• Experience with Power BI semantic models and direct lake mode
• Exposure to Azure Purview for data cataloging and lineage
• Experience with real-time data processing (Event Streams in Fabric, Azure Event Hubs)
• Prior consulting or client-facing experience delivering solutions across multiple industry domains