Data Engineer

About the role

Our client, a large purpose-led organisation in the middle of a major data and technology transformation, is building out its data engineering capability and hiring Data Engineers to help shape the enterprise data platform.

This is a genuine build role. You will be ingesting project and legacy data, building and maintaining pipelines in Azure Data Factory, writing transformations in Python and PySpark, and helping shape a modern Databricks-based platform that powers reporting, analytics and decision-making across the business. You will work alongside data analysts, architects and application engineers in a collaborative, non-operational environment focused on insight rather than firefighting.

What you will be doing

• Building and maintaining data pipelines in Azure Data Factory
• Writing transformations in Python and PySpark within Databricks
• Ingesting and structuring project and legacy data to a clear standard
• Creating curated datasets to support reporting and analytics
• Contributing to data quality rules and automated testing
• Documenting pipelines and following good engineering practice

What we are looking for

• Proficiency in Python, including PySpark, for transformations
• Strong SQL
• Hands-on experience with Azure Data Factory
• Hands-on experience with Azure Databricks and a real understanding of its components
• Experience building data lake ingestion pipelines
• Around 3+ years in a data engineering role
• Nice to have: Azure Synapse, data quality/testing, Agile/Scrum, CI/CD

What is on offer

• Salary starting at £55,000, with some flexibility for the right person
• Largely remote working, with occasional on-site days in the Bradford area (as little as once or twice a month for a strong remote candidate)
• The chance to help build a data platform rather than just maintain one, inside a sizeable transformation programme
• A supportive, insight-focused team with no on-call or heavy operational support burden

Interested, or know someone who would be? Get in touch.