Monzo went from zero rules to one of the most opinionated data architectures in fintech — and cut warehouse costs by 40%+ doing it.
Bruno Campos, Analytics Engineer at Monzo, joins Harry to unpack the rebuild of Monzo's entire data platform — tens of thousands of dbt models, hundreds of teams, one BigQuery warehouse, and a migration that's still only 30-40% done.
Bruno breaks down Monzo's new "OOM" architecture: four fixed layers, data contracts between teams, and an internally-built tool (ModelGen) that turns a YAML file into standardised SQL. The result — faster builds, easier onboarding, and serious cost savings that show up on the GCP bill.
They also get into why "data" as a discipline is still, in Bruno's words, "incredibly immature" — and what it'll take to fix that.
In this episode:
Why Monzo moved from a free-form warehouse to a heavily opinionated one
The four-layer OOM model: landing, normalized, logical, presentation
Interface models — Monzo's version of data contracts between teams
How ModelGen automates standardisation across 100+ teams
The real cost and time savings from re-architecting at scale
Bruno's take on AI's role in analytics engineering — and why the job isn't going anywhere
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