We Had a Perfectly Good Data Store. That Was the Problem.
This title could be clearer and more informative.Try out Clickbait Shieldfor free (5 uses left this month).
A data engineering practitioner shares lessons from migrating enterprise reference data from a MongoDB operational store to a governed data product platform. The core insight: the data was never broken — the architecture was asking an operational store to serve analytical consumers, which it was never designed to do. The solution involved three key decisions: keeping MongoDB as the authoritative golden source (no rip-and-replace), consolidating four independent extraction pipelines into one canonical path (MongoDB → Kafka Connect → Landing/Bronze/Silver Iceberg tables on S3 → Athena → Data Marketplace), and treating publication as a first-class pipeline stage rather than an afterthought. The post emphasizes that the hardest problems were social and organizational — naming conventions, provenance columns, ownership clarity, and discoverability — not the technical pipeline components. The key architectural principle: separate truth (MongoDB), transport (pipeline), and consumption (product layer) as three distinct concerns.
