Data Hatch
One platform partnership, earned on certified engineers and shipped engagements. Most of our lakehouse work runs on Databricks because the alternative, five tools wired together, costs more and breaks more.
Databricks
Designing, migrating, and operating production lakehouses.
Design from scratch or migrate from a fragmented legacy estate. Delta Lake medallion (bronze / silver / gold), Delta Live Tables for declarative pipelines, and a sourcing model that doesn't lock you to a single cloud.
The governance layer that lets you actually share data without a quarterly access-review fire drill. Lineage that auditors accept; row- and column-level security; tag-based policies that scale with the org.
Production ML and GenAI on the same platform as the data. Feature store, model registry, MLflow tracking, online serving with auto-scaling and request logging. Evaluations wired into CI, not bolted on after launch.
The unglamorous half. Drift monitoring, retraining schedules, runbooks, and on-call rotations your team can actually run. We hand back a system, not a slide deck.
A five-tool data stack means five contracts, five failure modes, and every integration is a future incident. Databricks consolidates the lakehouse, governance, and ML serving into one operational surface, exactly the shape of system we like to hand over.
One platform to monitor, patch, secure, and explain. Not five.
Models live next to the data they were trained on. No cross-system schema drift.
Every table, model, and dashboard traceable to source. Audit becomes a query, not a project.
If you're consolidating a fragmented estate or building from clean slate, we'll spend a session pressure-testing the idea. No slide deck.
Book a working session ↗