Data platforms, built to run.
I'm Maurits — a data engineer — helping companies make better, data driven decisions by centralizing their data into a modern data platform.
Twelve engagements. One way of working.
I'm a data engineer who helps companies make better, data driven decisions by centralizing their data into a modern data platform. Once the numbers live in one trustworthy place instead of scattered across exports and disconnected systems, a business stops debating whose spreadsheet is right and starts asking sharper questions — where is margin actually slipping, which customers are worth chasing, what's about to break before it does. Twelve engagements across retail, industry, healthcare and HR have all pointed at the same outcome: data that a business is genuinely curious about, rather than data it has to be talked into using.
Where I plug in
Data platform architecture & build
Greenfield data platforms designed from source system to reporting layer, with engineering standards — CI/CD, version control, testing, cost monitoring — built in from day one.
Warehouse migration & modernization
Moving off legacy on-premises warehouses onto Azure, Databricks, Fabric or Synapse, without a break in reporting continuity for the business.
ELT pipeline engineering
dbt, Data Factory and reverse-ETL pipelines, dimensional modelling with Kimball and Data Vault, and streaming pipelines in Spark Structured Streaming.
ERP & SaaS integration
Getting clean, reliable data out of SAP, Workday and Microsoft Navision — and back in again, where a reverse-ETL flow is what the business actually needs.
Analytics & AI advisory
Build-vs-buy decisions, architecture reviews, and LLM- or NLP-based analytics layered on top of a platform that's actually ready for them.
Technical assessments & change management
Auditing an existing platform against its actual technical debt — pipeline reliability, test coverage, cost, ownership gaps — and turning that into a concrete, sequenced roadmap the engineering team can execute without stalling production.
Notes from recent engagements
The five things I check before I call a data platform “modern”
Scalability, governance, agility, literacy, quality — the same five things I've checked on every engagement, whether or not agentic AI is anywhere near the project.
2 Mar 2026Engaged by data, not overwhelmed by it: what Lakebase and Genie Spaces change
Most businesses don't have a data shortage — they have a dashboard surplus. Databricks' Lakebase and Genie Spaces attack that problem from two different angles.
10 Feb 2026Kimball or Data Vault: how I actually choose
Both modelling approaches get pitched as universal answers. In practice the right one depends on how many source systems you have and how fast they change.
14 Jan 2026What migrating off an on-premises warehouse actually looks like
The technical migration is rarely the hard part. The hard part is keeping every report correct while you do it.
22 Nov 2025Where LLMs actually help in a data platform (and where they don't)
Not every analytics problem needs a language model. The ones that do tend to share one thing in common: unstructured text.
Have a data platform that needs building, or fixing?
I take on a small number of engagements at a time, usually starting with a short scoping conversation. Based in Ghent, working across Belgium and remotely.