Azure Data Engineer with Microsoft Fabric

Key Responsibilities:

• Design and develop end-to-end data engineering solutions using Microsoft Fabric (Dataflows Gen2, Pipelines, Lakehouse, OneLake).
• Build and manage data ingestion pipelines using Azure services such as ADLS Gen2, Azure Data Factory, Azure Synapse, Event Hubs.
• Develop Notebooks using PySpark/Spark SQL for data transformation and validation.
• Implement and optimize Lakehouse architectures using Delta/Parquet formats.
• Create and maintain Semantic Models in Fabric for reporting and BI consumption.
• Implement secure access using RBAC, Key Vault, Managed Identity, and follow best practices for PII protection.
• Improve performance through partitioning, indexing, and workload tuning within Fabric.
• Build CI/CD pipelines using Git & Azure DevOps for data engineering workflows.
• Collaborate with business, analytics, and architecture teams to deliver scalable data solutions.

Required Skills & Experience:

• Experience in Data Engineering.
• Strong hands-on experience with Microsoft Fabric (mandatory).
• Proficiency in Azure Data Services: ADLS Gen2, ADF/Synapse, Azure SQL.
• Expertise in SQL, PySpark, Spark SQL, and Delta Lake.
• Experience with Pipelines, Dataflows Gen2, Lakehouse, Notebooks in Fabric.
• Understanding of data modeling, data warehousing, and semantic layer design.
• Working knowledge of DevOps practices, Git, CI/CD pipelines.
• Experience in data governance, Purview, lineage, and metadata management.
• Strong understanding of security: RBAC, Key Vault, encryption, PII handling.

Good to Have Skills:

• Certifications: DP203 (Azure Data Engineer) or DP600 (Fabric Analytics Engineer).
• Experience with Power BI (DAX, RLS, semantic model optimization).
• BFSI/Financial domain experience.
• Experience with Databricks or Synapse Spark environments.