Data Engineering
Your data made usable: pipelines connecting every tool to one source of truth, cleanup and dedup rules that keep it trustworthy, and scraping where the data you need doesn't exist yet.
Free audit first. No deck — just the plan.
The scope
- Source audit
- Warehouse setup (right-sized)
- Automated pipelines + syncs
- Cleanup + deduplication rules
- Scraping / enrichment jobs
- Pipeline monitoring option
The process
Audit your sources
GHL, Shopify, Stripe, ad platforms, analytics, accounting — we map what data exists, what's clean, what's missing.
One source of truth
Centralize into a warehouse (Postgres, BigQuery, or simple Sheets if scale doesn't warrant). Maintained by agents, not a manual export.
Pipelines, not exports
Automated syncs keep every tool feeding the store on schedule — no one's Tuesday is spent downloading CSVs.
Fill the gaps
Where the data you need doesn't exist yet, scraping and enrichment jobs create it — competitor prices, directories, market lists.
Build + Run engagement
This starts as a scoped build — and can end with us running what we built, on a monthly tier. Most clients take the handoff; it's optional.
The Data system
Clean, connected, and ready to use. Every data engineering engagement runs on this operating system — see the full problem, approach, and deliverables.
Explore the system