Description

You will design and implement ETL pipelines using Microsoft Fabric and Azure Data Factory to build scalable data solutions.

This role is on-site.

Responsibilities

• Build and maintain a metadata-driven Lakehouse architecture with threaded datasets for multiple consumption patterns.
• Develop agent-specific data lakes and an orchestration layer for an uber agent querying across agents.
• 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.
• Strong expertise in Microsoft Fabric components: Lakehouse, Dataflows Gen2, Pipelines, and Notebooks.
• Proficiency with Azure Data Factory, Azure SQL, and Azure Data Lake Storage Gen2.
• Hands-on experience with SQL, Python, and PySpark/Scala.
• Ability to build metadata-driven architectures and reusable components.
• Experience handling structured and semi-structured data formats (JSON, XML, CSV, Parquet).
• Strong understanding of data modeling, governance, and security best practices.
• Executive-level written and oral communication skills.

Preferred Skills

• Familiarity with agent-based architectures and conversational AI integration.

Key Skills

Education

Any Graduate