About this role
Primary Skills Good To Have Skills Role Microsoft Fabric (Lakehouse, Warehouse), Azure Synapse Pipelines, and Azure Enterprise Data Warehouse (EDW Experience with Azure DevOps, PowerBI, GitHub, or other CI/CD pipelines. Data Engg Lead Summary: We are seeking a highly skilled Data Engineering Lead to drive the design, development, and delivery of enterprise-grade data and analytics solutions using Microsoft Fabric (Warehouse, Lakehouse), Azure Synapse Pipelines, Azure Enterprise Data Warehouse (EDW), This role involves leading a team of data engineers and analysts, working closely with stakeholders, and architecting scalable solutions across modern Azure data platforms. Key Responsibilities: Lead end-to-end data engineering efforts including design, development, deployment, and optimization of data pipelines and warehouse solutions on Azure. Implement and scale Microsoft Fabric workloads (Lakehouse, Warehouse, Dataflows Gen2, OneLake, Notebooks, Pipelines). Architect and manage scalable Azure Synapse Pipelines (SQL and Apache Spark) for ingesting, transforming, and loading large volumes of structured and semi-structured data. Oversee Azure EDW (Dedicated SQL Pools) design, data modeling, and performance tuning. Drive Power BI semantic model design, DAX development, and dashboard/reporting best practices across the organization. Collaborate with business and technical teams to understand data requirements and ensure solutions are aligned to enterprise goals. Manage data governance, metadata, quality, and security in compliance with organizational and regulatory standards. Provide technical mentorship and guidance to data engineers and BI developers. Establish DevOps/CI-CD practices for version control, deployment, and monitoring. Stay up to date with new Azure/Fabric features and recommend improvements. Required Skills & Experience: 10+ years of experience in data engineering and business intelligence. Strong hands-on expertise in: Microsoft Fabric (OneLake, Lakehouse, Warehouse, Pipelines, Dataflows Gen2, Notebooks) Azure Synapse Analytics (SQL Pools, Spark Pools, Pipelines) Azure Data Lake (Gen2) and Azure EDW Proficiency in SQL, T-SQL, and Apache Spark (PySpark or Scala). Deep understanding of data warehousing concepts, dimensional modeling, and data Lakehouse architecture. Strong experience with performance tuning and enterprise-scale data architecture.