Unlock the real value of data and AI.

Our world runs on PySpark, Delta Lake and Microsoft Fabric. We build the data platforms our clients actually run their business on ,not proof-of-concepts that demo beautifully and quietly die three months later. Platforms people trust enough to make real decisions with.

Moving data from A to B is the easy part. Making sure someone at the other end understands where the number came from, believes it, and can maintain the thing after we've gone, that's the vigente job.

So we're looking for a Data Engineer who'd rather ask one good question than build three unnecessary pipelines.

What you'll do

Some weeks you're deep in Spark notebooks working out why a four-minute job takes forty. Other weeks you're at a whiteboard with a business owner, because nobody in the organisation agrees on what "active customer" means. Both of those are the job.

Depending on the project, you'll:

- Build lakehouse architectures in Microsoft Fabric that survive contact with real data
- Model, transform and optimise data for analytics and AI and argue about the model before building it
- Write PySpark and SQL that the next person can actually read
- Sit in the architecture discussions; your opinion counts from week one, with no layer between you and the decision
- Design pipelines on Delta Lake, medallion where it earns its keep, something simpler where it doesn't
- Work side by side with our architects, our analysts and the client's own team
- Leave behind something the client can run without us

No two projects are the same. They all have one thing in common:



you stay close to the business problem you're solving.

What we're looking for

We're more interested in how you think than in checking every box. You probably recognise yourself in most of these:

- SQL and Spark are comfortable territory
- You're curious about AI and honest about where it doesn't help yet
- You can explain a technical trade-off to someone who's never opened a notebook
- You follow the problem, not the ticket
- You share what you learn, with the team, at a meetup, or on a stage
- You think the best solutions get built together, not handed over
- You've built data solutions that made it to production (Fabric or Azure preferred, but if you've done it well somewhere else, we'll happily talk)

Why mind the facts?

We started mind the facts with a simple ambition: to do better. You'll work directly with the people who started it, a small team on purpose. No layers, no account manager relaying your ideas upward; you're in the conversation.

Most days you're where the impact is: at the client or remote. Once a month we get everyone together to swap what we've learned, argue about architecture and simply reconnect. We're active in the Belgian data community, user groups, meetups, conferences, because knowledge is shared, not hoarded. And we stay involved after go-live, because consulting works better when you're still there to see what actually happened.

Better consulting. Better conversations. Better collaboration.

Sounds like you?

We'd love to hear your story. Start with a conversation: [email protected]

📌 Microsoft fabric data engineer (España)
🏢 mind the facts
📍 España