Description

Data Product Engineer

Contract Length: 6 months

Engagement: Inside IR35

Days on site: 1-2 days a week

Interview stages: 2 stages

A long-established financial institution with a strong reputation for stability and innovation is investing heavily in its data transformation strategy. With a mission to better understand customers, manage risk, and unlock data-driven opportunities, the organisation is building a modern cloud-based data platform to support analytics, reporting, and AI initiatives.

The Role

As a Data Product Engineer, you'll be at the heart of building the bank's Common Data Model - a governed, reusable foundation of core entities such as Customer, Account, and Transaction. Using Databricks, Delta Lake, and Microsoft Fabric, you'll design and deliver high-quality, well-documented data products that embed trusted business logic and serve as a single source of truth across the organisation.

What You'll Do

• Design, build, and maintain data products and pipelines on Databricks and Fabric.
• Develop performant transformations in Spark SQL and Delta Lake.
• Collaborate with business SMEs, analysts, and data modellers to translate requirements into reliable assets.
• Apply governance and metadata standards using Unity Catalog, Purview, and Fabric.
• Optimise performance and ensure resilience of services in a regulated environment.
• Contribute to data engineering standards and mentor within the data community.

What We're Looking For

• Proven experience engineering on Databricks (Azure preferred) with Delta Lake.
• Strong Spark SQL skills, with ability to deliver maintainable queries at scale.
• Experience building modular data models and applying complex business logic.
• Understanding of data modelling techniques (canonical, vault, dimensional).
• Familiarity with metadata and governance frameworks such as Unity Catalog.
• Strong communication skills to work across technical and non-technical teams.
• Background in regulated industries (banking, insurance, healthcare) is an advantage.

Nice to Have

• Exposure to AI/ML data workflows.
• Familiarity with Microsoft Purview.