A legacy warehouse, rebuilt in the cloud

Context

A market data business needed to move off a legacy platform that had become expensive to run and slow to change. The requirement was not simply a lift-and-shift: performance, scalability and cost-efficiency all had to improve, and the migration had to happen without interrupting a product that customers depend on.

The problem

Legacy platforms accumulate undocumented dependencies. Nobody could give a complete account of what consumed what, which made any cut-over risky. Deployment was inconsistent across workflows, so changes behaved differently depending on who shipped them and when. There was no reliable lineage, which made both debugging and governance largely manual.

What we did

• 01Architected the target cloud platform and warehouse, sized and structured against a cost model agreed up front.
• 02Rebuilt the pipelines around a managed orchestrator and a version-controlled transformation layer, so logic lived in reviewed SQL rather than in scattered scripts.
• 03Managed the entire infrastructure as code, making environments reproducible and changes reviewable.
• 04Designed CI/CD processes that applied uniformly across every data workflow, removing the it-depends-who-deployed-it class of failure.
• 05Established governance, lineage and reliability practices with the cross-functional teams as part of the build rather than as a later phase.