Data function as a service
The data department your company does not have yet
I build your data function from zero, run it in production, then hand it over working and trained on your own stack. One service, three ways in. Built to keep running without me. No lock-in.
Build
I create your data function from zero: the architecture, the governed metric definitions, the pipelines, and the dashboards your team actually trusts. You get production systems, not a slide deck.
Fix
You already have a data setup, but it does not deliver. I get it back on track: untangle the stack, fix what is broken, and make the numbers trustworthy again so people stop second-guessing every report.
Handoff / Run
Once it works, you choose. I hand the function over to your team, trained on your own stack and documented, or I stay on to run it. Either way it is built to keep working without me.
Who it is for
Startups and scale-ups in Europe that have outgrown spreadsheets but cannot yet staff a full data team. You have the data, it just does not answer any question, and a wrong first data hire would cost you a year. That is the gap I cover.
Built to run without me
Most outside help leaves you dependent on it. I do the opposite. Everything is built on standard, portable tools, documented, and handed over to your people trained on your own stack. The test is concrete: the function keeps running when I step away. That is what separates this from a system integrator, and it is the whole point, not a footnote.
Frequently asked questions
What is a data function as a service?
A data function as a service is the whole data department of a company, delivered by an external operator instead of hired in-house. I design the architecture, build the pipelines and dashboards, run them in production, and then hand the function over to your team trained on your own stack. You get the outcome of a data team without having to recruit and manage one from scratch.
How is this different from hiring a fractional head of data?
A fractional head of data gives you part-time leadership for a team you already have. A data function as a service gives you the whole function when you do not have one yet: leadership, build, and run. If you already have a team that just needs direction, I can also step in as fractional data leadership, but the default is end to end.
How is this different from a system integrator or a staffing agency?
Staffing rents you hands that leave when the contract ends, and the knowledge leaves with them. A system integrator often builds something only they can maintain. I build the function to keep running without me: documented, on standard open tools, and handed over to your people. No lock-in is the point, not a footnote.
When should I build a data team in-house versus outsource it?
Build in-house when data is core to your product and you can attract, pay, and manage senior data people today. Outsource the function when you have outgrown spreadsheets but a wrong first data hire would cost you a year. I bridge that gap: I run the function now and hand it over when internalizing it actually makes sense.
Who do you work with?
Startups and scale-ups in Europe that have outgrown spreadsheets but cannot yet staff a full data team. Usually post product-market-fit, where decisions are getting expensive and the data exists but does not answer questions.
What happens at the end of an engagement?
Either I hand the function over to your internal team, fully documented and trained on your stack, or I stay on a lighter retainer to maintain and evolve it. The architecture and the people are yours. The test is simple: the function keeps running when I step away.
