Boring, traceable data work that you can trust.

One reconciled dataset. Predictable refresh. A runbook you can hand to someone else.

What you get

• One reconciled dataset with explicit rules and documented assumptions
• Predictable, repeatable refresh you can schedule and trust
• A runbook covering run steps, edge cases, and key decisions
• Clean handoff — your team can operate it after I leave

What I need from you

• Access to the source systems (read-only is fine to start)
• Exports, schemas, or sample data for each source
• A list of the tools in your stack
• One decision owner who can confirm scope and sign off on done

How it works

1. Intake. You share sources, formats, and known problems. I inventory what exists.
2. Scope. We agree on what moves where, what "done" means, and a definition of done in writing.
3. Build. I build the pipeline — extraction, normalization, reconciliation, scheduling.
4. Document. I write the runbook: run path, edge cases, failure modes, key decisions.
5. Handoff. One walkthrough. You run it. I answer questions for a short window after delivery.

Definition of done

• Pipeline runs without manual intervention
• Output matches the agreed structure and passes agreed checks
• Runbook is complete and reviewed
• Handoff walkthrough is done
• You can run it yourself

Good fit

• Data is spread across multiple systems with no reliable join
• Manual exports and repeated spreadsheet cleanup are routine
• IDs or categories do not line up across sources
• Someone on your team is stuck in break-fix work instead of finishing pipeline work
• You need a bounded, finishable slice of work — not a long retainer

Not a fit

• You need analytics interpretation, dashboards, or conclusions drawn from data
• The scope is open-ended with no definition of done
• You need embedded staff, not a project delivery

Ready to start?

Send a short note with your source systems and what you need to land where. I will reply with scope questions.