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.

- Solid 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.

📌 Fabric Data Engineer (Hyderabad)
🏢 Latentview
📍 Hyderabad