From Stored Procedures to Scalable Data with Zopa

Date: February 24th

Time: 10:00am GMT

As organisations grow, analytics must evolve with them. For Zopa, legacy stored procedures had become a constraint rather than an accelerator. Business logic was opaque, documentation was unreliable, and change depended on a small group of specialists. At the same time, regulatory expectations were increasing and analytics needed to scale beyond a central data team.

In this session, Zopa shares how it modernised its analytics stack by moving from stored procedures to an analytics engineering workflow built on dbt. By standardising on modular, tested, version-controlled models with dbt Core, and later adopting the dbt Platform, Zopa reduced risk, improved delivery speed, and enabled governed self-serve analytics across teams.

You’ll learn how Zopa moved from brittle, hard-to-change pipelines to a scalable hub-and-spoke model using dbt Mesh. Live documentation, column-level lineage, and built-in CI replaced manual processes and stale Confluence pages, increasing trust in analytics and supporting both product decision-making and regulated reporting.

This session is a practical look at how modern analytics engineering enables scale, governance, and confidence in data.

Francis Nwobu

Senior Analytics Engineer

Zopa Bank

Carlos Castro

Staff Solutions Architect

dbt Labs

Tayo Moore

Senior Analytics Engineer

Zopa Bank