Data Architect

Location: London

Working model: Hybrid

This contract sits within a major data platform transformation programme, driven by regulatory pressure and the need to modernise legacy data estates. The work is focused on building a scalable, metadata-driven data platform that supports enterprise-wide analytics and reporting.

The engagement is delivered via a leading consultancy, embedded within a well-established financial services organisation. You’ll be working alongside senior architects, platform engineers, and data teams to shape a Databricks-led ecosystem that is actually fit for purpose, not just another lift-and-shift exercise.

This is a 6 to 12 month contract, operating on a hybrid basis in London. The role is design-led but expects someone who can operate close to the code when needed. You’ll own solution design across the platform, ensuring patterns are robust, repeatable, and deployable.

The environment is centred around Databricks, with a strong emphasis on metadata-driven processing, lineage, and structured data layers across Raw, Generic, and Business domains. The programme is moving at pace, so designs need to be pragmatic, not academic.

You’ll be responsible for defining architectural patterns, guiding multiple delivery squads, and ensuring consistency across the platform. This includes shaping frameworks, reviewing implementation, and stepping into technical detail where required, particularly around Python and workflow orchestration.

Key Skills & Experience:

• Strong experience designing enterprise data platforms, ideally on Databricks
• Proven track record delivering metadata-driven architectures and data lineage models
• Hands‑on capability with Python in data platform or engineering contexts
• Experience defining data layer architectures across Raw, Curated, and Business layers
• Solid understanding of Databricks Workflows and orchestration patterns
• Ability to operate across multiple squads, providing architectural governance and direction
• Experience working within regulated environments, ideally financial services

If you’ve designed data platforms that actually get used, rather than just documented, this is worth a conversation.

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