Service / 09
Data
Engineering
The pipes, warehouses, and pipelines that keep every downstream metric honest.
ETL · Warehousing · Pipelines
99.9%
Pipeline uptime
<1h
Freshness SLA
100%
Tested transforms
Overview
Reliable analytics and ML start with reliable data. We design ingestion, transformation, and warehouse layers that scale — and we instrument them so you trust the numbers.
What you get
Deliverables.
Source-to-warehouse pipelines
Warehouse schema & modeling
dbt or SQL transform layer
Orchestration (Airflow / Dagster)
Data quality tests & alerts
Documentation & lineage
How we work
Process.
- / 01
Audit
Map every source, every consumer, every silent failure.
- / 02
Design
Schema, modeling layer, orchestrator — built for the next 3 years.
- / 03
Build
Ingest, transform, test. Document as we go, not after.
- / 04
Operate
Alerts, lineage, and runbooks so on-call doesn't dread it.
FAQ
Things people
always ask.
Which warehouse do you recommend?
BigQuery and Snowflake for most teams; Postgres when scale doesn't justify the cost.
Do you use dbt?
Yes — dbt is our default for the transform layer, with tests and docs on every model.
Ready to
build it?
Tell us what you have in mind. We'll come back within 24 hours with a clear-eyed take and next steps.
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