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.
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Implement and scale Microsoft Fabric workloads (Lakehouse, Warehouse, Dataflows Gen2, OneLake, Notebooks, Pipelines).
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Architect and manage scalable Azure Synapse Pipelines (SQL and Apache Spark) for ingesting, transforming, and loading large volumes of structured and semi-structured data.
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Oversee Azure EDW (Dedicated SQL Pools) design, data modeling, and performance tuning.
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Drive Power BI semantic model design, DAX development, and dashboard/reporting best practices across the organization.
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Collaborate with business and technical teams to understand data requirements and ensure solutions are aligned to enterprise goals.
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Manage data governance, metadata, quality, and security in compliance with organizational and regulatory standards.
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Provide technical mentorship and guidance to data engineers and BI developers.
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Establish DevOps/CI-CD practices for version control, deployment, and monitoring.
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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.
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Strong hands-on expertise in:
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Microsoft Fabric (OneLake, Lakehouse, Warehouse, Pipelines, Dataflows Gen2, Notebooks)
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Azure Synapse Analytics (SQL Pools, Spark Pools, Pipelines)
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Azure Data Lake (Gen2) and Azure EDW
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Proficiency in SQL, T-SQL, and Apache Spark (PySpark or Scala).
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Deep understanding of data warehousing concepts, dimensional modeling, and data Lakehouse architecture.
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Strong experience with performance tuning and enterprise-scale data architecture.
