Fabric Data Engineer

Role & responsibilities

• Lead the design, development, and deployment of scalable data pipelines using Microsoft Fabric Data Factory, Dataflows Gen2, and Spark Notebooks.
• Implement and optimize Medallion Architecture (Bronze/Silver/Gold) using Delta Lake, OneLake, schema evolution, and partitioning strategies.
• Drive data migration and integration from Azure Synapse, SQL Server, Databricks, and Snowflake into Microsoft Fabric.
• Build batch, streaming, and real-time data pipelines using Fabric Real-Time Intelligence, Eventstreams, KQL Database, and Eventhouse.
• Design and optimize data models and Power BI semantic layers, leveraging Direct Lake, Import, and DirectQuery for high-performance analytics.
• Establish data governance, security, CI/CD, Git integration, automated testing, and deployment standards, including Microsoft Purview for lineage and cataloging.
• Provide technical leadership and mentorship to data engineers through code reviews, architectural guidance, documentation, and engineering best practices.

Preferred candidate profile

• 7+ years of experience in Data Engineering, Data Platform Development, or ETL Architecture.
• 1.5+ years of hands-on experience with Microsoft Fabric.
• Strong hands-on expertise in Microsoft Fabric, OneLake, Lakehouse, Warehouse, Data Factory, and Real-Time Intelligence.
• Strong programming skills in Python/PySpark and SQL/T-SQL.
• Knowledge of M, PowerShell, or Azure CLI.
• Strong understanding of Apache Spark, Delta Lake, Medallion Architecture, data lakehouse patterns, partitioning, and performance optimization.
• Expertise in data modeling, including Kimball methodology, dimensional modeling, and star schemas.
• Hands-on experience with Azure DevOps/GitHub Actions, Fabric Deployment Pipelines, Git, CI/CD, and Microsoft Purview.
• Experience with Power BI semantic models, DAX, Direct Lake, Import, and DirectQuery.