Reliable data pipelines, from source to warehouse.
We build the infrastructure that moves data from source systems into analytics-ready storage. Source connectors, transformation layers, and warehouse schemas are designed around the queries your team runs, not generic star schemas that require extra view layers to answer common questions.
Every pipeline ships with monitoring, retry logic, and a schema shaped around your business's reporting needs, not a textbook normal form.
Database CDC, API polling, file drops, webhook receivers. Each source lands in a staging layer, then SQL-first models transform it into reporting-ready tables with a test suite that runs before promotion.
Warehouse schemas are designed around the queries your team actually runs. Wide tables, materialized views, and pre-aggregations keep dashboards loading in seconds, not minutes.
Pipeline observability from day one. Row counts, freshness checks, schema drift alerts, and SLA tracking so problems surface to the team that built the pipeline before they surface to the people who depend on it.
Idempotent loads mean any time range can be reprocessed without duplicates. Airflow or Prefect orchestration with retry policies, dependency graphs, and centralized logs turns backfills into a config change, not a weekend war room.
Tested and deployed connectors for every data source your business uses, with credential rotation and error handling built in.
Versioned SQL models with tests, documentation, and a promotion workflow that prevents untested changes from reaching production.
A schema designed for your team's actual queries, with materialized views and pre-aggregations where they matter.
Operational documentation covering failure modes, backfill procedures, and escalation paths, written for the person who'll be on call.
Book a discovery call. We will walk through how this fits your business, scope, timeline, and what you will get at the end.