About

Background

I'm a programmer in the broad sense: most of my energy goes into pipelines and sync that scale well and tooling that stays understandable for both end users and developers. I have applied this approach to research in several areas, geospatial domain and in HR/payroll systems.

Focus

  • Python
  • Pipelines & sync
  • Spatial / GIS
  • Analysis & perf

Chapters

  1. Origin

    Grew up on Goeree-Overflakkee, a small island in the southwest of the Netherlands.

  2. BSc Physics

    Studied physics, with a focus on gravitational waves and theoretical physics. I loved using mathematics to solve and explain physical phenomena that can be hard to see or understand at first glance. In physics I learned that the best way to understand a complex system is to break it into components, and that those components can often be described in simpler, analogous ways.

  3. Internship · ASML

    First industry experience: Breaking down a complex system into its components and data to understand how inefficiencies in running DUV lithography tools can be mitigated. Used matlab to pipe data from the machines into presentable reports.

  4. MSc Applied Data Science · Utrecht University

    Applied Data Science, thesis completed in 2025 in cooperation with Open Future. Built an NLP pipeline on ~53k EU Horizon project descriptions, released a Python package for SEDIA API access, and introduced a funding-weighted metric for rhetorical drift in climate-related research.

  5. Geo IT Developer · dBvision

    Developed and maintained the QdB QGIS plugin and its Python package for acoustic consulting. Work included ETL across data formats and GIS systems, centralized via one tool and a GeoPackage data mode inside QGIS. QGIS is open-source GIS software, while it is great for general purposes, it did not have native tools for accoustic modeling and it did not handle Z/M values reliably, so I built custom tools that still scaled to large geospatial datasets. Geospatial work appealed to me because data arrives in many formats and often in a very large scale, keeping heavy calculations within acceptable runtimes was often the hardest part of the job, and I like solving that kind of performance problem.

  6. Since May 2025

    Python Data Developer · BrynQ

    Building, testing and distributing Python integrations in the HR/payroll ecosystem, including systems like Afas, Workday, Zenegy, Nmbrs, Hibob, Factorial, Sage 100 Fr and many more. I did not build one-off solutions, but my focus was on making general solutions that could be applied for any customer and any project. This also resulted in a generalised backend layer that applies data transformations between arbitrary systems based on what each customer selects in the UI, with declarative mapping specs and regression tests instead of one-off intergration scripts, with a big focus on making it easy to use and maintain by collegue developers, now the standard of how we work with data integrations at BrynQ.

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