Description

You will design and implement ETL pipelines using Microsoft Fabric and Azure Data Factory to support a metadata-driven Lakehouse architecture.

This role is on-site.

Responsibilities

• Build and maintain a metadata-driven Lakehouse architecture supporting multiple consumption patterns.
• Develop agent-specific data lakes and an orchestration layer for cross-agent querying.
• Enable interactive data consumption via Power BI, Azure OpenAI, and other analytics tools.
• Ensure data quality, lineage, and governance across all ingestion and transformation processes.
• Optimize performance and cost across storage and compute layers.

Required Skills

• 7+ years of data engineering experience focused on the Microsoft Azure Data stack and Fabric.
• Expertise in Microsoft Fabric (Lakehouse, Dataflows Gen2, Pipelines, Notebooks) and Azure Data Factory.
• Strong proficiency in SQL, Python, and PySpark/Scala.
• Experience with Azure SQL, Azure Data Lake Storage Gen2, and Power BI.
• Hands-on experience with structured and semi-structured data (JSON, XML, CSV, Parquet).
• Proven ability to build metadata-driven architectures and reusable components.
• Strong understanding of data modeling, data governance, and security best practices.

Key Skills

Education

Any Graduate