About

Ramses Kools

I'm an AI and data engineer based in Amersfoort, Netherlands. I currently work as a Senior AI Engineer at Future Facts, a data and AI consultancy that is part of the Hot ITem Groep, which in turn is part of Conclusion.

My background is a bit unusual for someone in this field. I studied Chemistry at the University of Amsterdam and completed a Bachelor and Masters degree. My master specialised in computational and theoretical chemistry, which meant building simulation algorithms in C++, running large workloads on compute clusters, and extracting insight from the produced data. That research mindset, writing code for complex systems and communicating results clearly, is something I still bring to engineering work today.

After graduating in 2019 I joined Zenz Technologies, a software company in Amsterdam building decision support systems for businesses worldwide. There I worked as a consultant and developer, implementing and customising data processing and visualisation tools for clients, as well as developing the in-house-build C++ libraries.

In February 2022 I joined Future Facts, where I have been ever since. Through Future Facs, I have worked with two major companies:

KLM (2022 - 2024) At KLM I was embedded in a software development department in a hybrid role spanning data engineering, DevOps, and software development. My work included modernising the C++ development toolchain and CI/CD practices, contributing to an automatic passenger rebooking system in C++, and working on a machine learning prediction project as a data and AI engineer. I also helped establish a C++ software engineering community within KLM.

PostNL (2024 - present) At PostNL I work as an AWS Data Engineer, helping develop and maintain a data warehouse environment that supports multiple business units in their data-driven decision making. The stack centres around Redshift, AWS CDK, Glue, Lambda, dbt, and Databricks. The work involves everything from data modelling and pipeline development to infrastructure as code and stakeholder management. At the moment I'm fully focused on migrating and rebuilding everything from the AWS-Redshift environment to a new dbt-cloud + databricks environment

What I work on

My primary focus is on the full lifecycle of data platforms: architecture, ingestion, transformation, governance, and delivery to BI and analytics consumers. Day to day that means working with dbt and Databricks as the transformation layer, Redshift and Iceberg as storage, and AWS CDK for infrastructure. I write mostly SQL and Python, with GitHub Actions handling CI/CD across projects.

I have been migrating existing ETL architectures toward a modern lakehouse model (Bronze/Silver/Gold), and alongside that I have been developing internal tooling, quality frameworks, and engineering standards to support that shift.

On the AI side, my work at Future Facts increasingly involves applied LLM tooling: integrating language models into workflows, building internal AI tooling, and helping clients understand how to move from experimentation to production.

Certifications

Outside work

I'm working on a 'homelab', which is a small micro-pc in our closet, that runs a number of self-hosted services. I enjoy tinkering with this machine and consider it my personal private digital playground. Currently, I'm running a number of media related services for my personal videos, photos, movies and series.

I enjoy electronic music and festivals (meet me at Lentekabinet), science fiction audiobooks, and video games.