A practitioner's guide to federated dbt Mesh at scale with Data Project Factory

Scaling data analytics at Kramp was once severely bottlenecked by a traditional, centralized Enterprise Data Warehouse model where a central Data Office owned all infrastructure and end-to-end business logic. This capacity deficit led to endless queues, massive technical debt, and a chaotic "Wild West" of custom BigQuery Scheduled Queries running under personal user credentials. 

Learn how Kramp’s data team removed bottlenecks, reduced domain provisioning from five working days to one, and drove governed scale with federated dbt Mesh across 25+ data projects and 50+ developers. We’ll show you how we built a "Data Project Factory”, an internal, automated GitOps engine that provisions a fully isolated, secure, and production-ready dbt stack, so you can roll out data quality gates and workflows at scale.