ETL and data pipelines
I design how data moves from source to report, and define what each field means. If you want, I build the first version myself.
Book an intro call
Always included
Architect-lead
Add when you want it
Hands-on build
You choose
Which parts
What I build
Four parts of a dependable pipeline
Data sources
Pulling data from the tools where it lives.
Transformation
Cleaning and reshaping it on a schedule you can trust.
Quality checks
Checks that flag a broken or late feed before anyone reads a wrong number.
Documentation
Plain documentation so the next person can read and extend the flow.
How it works
Design the flow, or design and build it
Step one, always
Architect-lead
I design the pipeline, set the field definitions, and direct whoever builds it, your team or a vendor.
Pipeline design for the sources you pick, field definitions and data checks, and a review of what gets built
Step two, added on top
Architect-lead plus hands-on build
Everything in step one, and I build the pipelines you choose myself. Costs more, because it is more of my time.
Working pipelines, not only a design, for the ones you choose, with a hand-off so your team can run them
Hands-on build always comes with the architect-lead work. You can take the architecture on its own.
Proof
Pipelines I have built
1
Feeds for a dozen business dashboards
Source data from billing, product usage, marketing and support brought into one consistent shape, so a dozen dashboards read from the same definitions.
2
Clean inputs for a long-range forecast
Conversion, retention, acquisition and session data prepared in one place, so a three-year forecast can rerun whenever planned features change.
3
One pipeline across many product teams
Built at multiple companies. One standard set of top-line KPIs for every product, with the next level of detail loaded behind it, so no team needs a custom pull.
4
Research and market data in one place
User research and market data brought alongside product data, so assumptions can be tested against more than one source.
Fit
Is this for you
A fit when
You have data spread across tools and need it moved and shaped reliably, with or without someone to build it.
Not a fit when
You want a one-off data export with no plan for who keeps it running. If you are not sure what is wrong, start with the Bottleneck Diagnostic.
Questions