Mid-Senior Data Engineer

About the role

This role supports the design, build, and optimization of a modern data platform. It focuses on developing scalable data pipelines and infrastructure that power analytics, reporting, and AI initiatives.

Responsibilities

• Design, build, and maintain ETL/ELT pipelines using Azure Data Factory and related tools.
• Architect and manage data lake and data warehouse solutions.
• Transform and move data across relational, NoSQL, and object storage systems.
• Collaborate with engineering and product teams to define data requirements and solutions.
• Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
• Ensure data quality and integrity across systems.
• Document data flows, schemas, and architecture decisions.
• Contribute to data platform strategy and ongoing improvements.

Requirements

• 3+ years of experience for mid-level candidates; 6+ years for senior-level candidates.
• Strong experience with Azure Data Factory or similar ETL/ELT tools.
• Solid understanding of database design (relational modeling, normalization/denormalization).
• Experience with data lakes and/or data warehouses (Azure Data Lake, Microsoft Fabric, etc.).
• Experience transforming structured, semi-structured, and unstructured data.
• Proficiency in SQL and experience with Azure SQL Database and/or Azure SQL Managed Instance.
• Familiarity with Azure data services and the Microsoft data ecosystem.
• Strong problem-solving skills and ability to work both independently and collaboratively.

Preferred Experience

• With Cosmos DB or other NoSQL platforms.
• Knowledge of KQL and Azure Monitor / Data Explorer.
• Experience with object storage and file-based data architectures.
• Exposure to analytics or data science tools (Databricks, Azure ML, etc.).
• Understanding of data governance, lineage, and cataloging best practices.