About
Most data problems are not modelling problems. They are provenance problems.
Nearly every failed reporting project I have been called into failed the same way: the number on the dashboard was wrong, nobody could say why, and by the time anyone traced it back the trust was gone. The model was fine. The lineage was not.
The short version
I design enterprise data platforms and the AI built on top of them. The interesting decisions are almost never about which model to use. They are about where the data comes from, who is allowed to see it, what fails the build when a schema drifts, and whether anyone can reconstruct a figure six months after the person who produced it has left.
That bias comes from the route in. I started in law and mechatronics, spent years in consulting doing valuations and BI, and came to architecture through the work rather than through a title. It leaves you sceptical of systems whose correctness rests on someone remembering a convention.
In practice
What that looked like.
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01 · PwC Österreich, 2022 — 2025
Making ERP data usable
Two years and eight months across BI consulting and tax technology. The recurring job was the same: take data locked inside BMD, Business Central or SAP, and turn it into something a controller could act on without re-keying it. Automation with RPA and Alteryx got the headlines; the durable part was the data models underneath.
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02 · CANCOM Austria, 2025 — 2026
Architecture at enterprise scale
Solutions architect for data and AI platforms, advising enterprise architects and C-level on strategy while still delivering the systems. Governance, security and scale designed in from the first diagram, because retrofitting them into a running platform costs an order of magnitude more.
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03 · ORBIS Austria, 2026 — present
Owning the platform and AI strategy
Principal Enterprise Architect for Data & AI: what gets built, on which stack, and how it is governed. Azure, Microsoft Fabric, AWS and Foundry, with the same question applied throughout — can we show why this number is what it is?
How I work
I still write code, and I intend to keep doing so. An architect who cannot read the pipeline they specified is guessing, and the guesses compound quietly until someone has to rebuild the thing.
I prefer enforcement to convention. A rule that lives in a document nobody opens is not a rule. Put it in the build — a schema test, a contract, a lineage check that fails — and it holds without anyone policing it.
The same instinct is why I ended up co-authoring work on governed coding agents: the question of how you prove a system did what it was asked is the same question, one layer up.
Where I fit
I am most useful where a platform strategy has to survive contact with a real migration — regulated industries, manufacturing, finance, the public sector. Places where a wrong number has a cost attached and someone eventually asks to see the derivation.
Based in Upper Austria, working across Linz, Wels and Vienna, and remote with distributed teams. If that sounds like your problem, here is how engagements usually start.
References
What others say.
Quotes go here once they have been cleared with the people who wrote them. The layout is finished; the words are not mine to publish yet.
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