Description

You will design and implement ETL pipelines using Microsoft Fabric and Azure Data Factory to support scalable data consumption patterns.

This role is on-site.

Responsibilities

• Build and maintain metadata-driven Lakehouse architectures with threaded datasets for multiple consumption patterns.
• Develop agent-specific data lakes and orchestration layers for AI agents to query across systems.
• 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 while collaborating with product teams.

Required Skills

• 7+ years of experience in data engineering with a focus on Microsoft Azure Data stack and Fabric technologies.
• Strong expertise in Microsoft Fabric, including Lakehouse, Dataflows Gen2, Pipelines, and Notebooks.
• Proficiency in Azure Data Factory, Azure SQL, and Azure Data Lake Storage Gen2.
• Experience with SQL, Python, and PySpark/Scala for 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.

Preferred Skills

• Familiarity with agent-based architectures and conversational AI integration.
• Experience with executive written and oral communication.

Key Skills

Education

Any Graduate