Introduction
You’ll join Quintel’s Modelling & Development team. This team works on the calculations, data and software behind the ETM. The data ranges from technology specifications, costs, and hourly profiles to representations of the complete energy system of more than 400 regions (the European countries, every Dutch province and municipality) for a reference year, built up from public sources. For a long time, this data was simply a requirement to run the ETM; increasingly, organisations come to us for the data itself.
The way we process that data has grown organically and should be structurally improved. The path from source to calculations is not yet a streamlined process: we want to move to pipelines that are fully script-based and modular. We have the time and resources to do this over the next four years. The goal is for our way of processing energy data to become the standard for the energy transition in the Netherlands and Europe: from EU level down to a neighbourhood or industrial site.
What you will work on
You will design the new pipelines, build them and, in time, take ownership of them. We’re deliberately looking for someone at the intersection of data engineering and data science: you build the infrastructure and take ownership on the subject matter. You know not only how the data flows through the system, but also what the numbers mean and when they’re wrong. What you build has to be traceable: every number can be traced back to its source. The team also has to be able to keep working with it. You build on what’s already there and only replace it when there are good reasons to do so.
Examples of what you’ll work on:
- Designing and building a new pipeline for the national datasets, merging two existing routes and aligning the data with international standards such as the Eurostat energy balances;
- Converting the regional datasets (municipalities, RES regions and provinces), hourly profiles and local data from loose notebooks and Excel files into a single reproducible, scalable pipeline;
- Building checks that make anomalies visible, both for us and for our users;
- Bringing hourly profiles, costs and technology specifications, and local data into the same structure.
Who we’re looking for
We’re looking for a new colleague for 32 to 40 hours a week, based in our Amsterdam office. You:
- have 2 to 5 years of relevant experience as a data engineer / scientist or in a comparable role, and a university degree in a relevant field such as data science, energy science, econometrics, physics or engineering;
- work comfortably with Python and Git, and can find your way around a complex Excel file or a GitHub repository;
- work analytically and systematically, with an eye for detail: one wrong unit propagates through hundreds of datasets;
- are proactive: you don’t wait for a task to land on your desk, but keep an overview of what others are working on and where the dependencies lie;
- are pragmatic: you improve what’s already there, step by step, rather than starting over;
- want to get to know the energy system well enough to understand where the data needs of a modeller, consultant or client come from;
- can explain clearly what is going on, in both Dutch and English.
- Ideally, but not essential: knowledge of energy statistics (such as energy balances or the Klimaatmonitor), experience with tooling for data pipelines or data validation (such as Dagster or Airflow), and experience with publishing open data.
You don’t need to tick every box already: we look at aptitude and the appetite to grow. Recognise yourself in most of these points? Then apply.
