“We exist because the problem was obvious —
and nobody was solving both sides of it.”
How we
got here.
A community. A paradox. A decision to do something about it.
The data engineering industry has a paradox. On one side, companies are investing heavily in data — modern stacks, cloud platforms, analytics, AI — yet they struggle to find engineers who can actually build, operate, and scale production-grade systems. Not because those engineers don't exist. But because there's no reliable bridge between the two.
“Thousands of talented engineers spend years learning — but lack real opportunities to apply that knowledge.”
We were born from a data engineering community that has spent years doing what most hiring platforms don't: teaching real-world data engineering, building hands-on projects that mirror production systems, and mentoring engineers through practical challenges. Over time, we built something valuable — a pipeline of capable, motivated, production-ready talent.
“Over time, it became clear: we were building a pipeline of capable, motivated, production-ready talent.”
At the same time, companies kept asking: do you know someone who can actually help us build this? That's when we realised: there is a gap here, and we're already positioned to close it. Datum was born from that realisation — not from a pitch deck, but from genuine need on both sides.
Five years of building.
Community founded.
We started teaching real-world data engineering online. Not courses — structured projects built to mirror production systems.
First project cohorts.
Engineers building production-style systems together. The community grew. The quality was obvious.
Mentorship programme.
Senior engineers began guiding the community. Real feedback on real code. Thousands of engineers improving together.
First clients.
Companies started asking. We delivered our first consulting engagements. The platform concept became clear.
Datum launched.
Consulting, hiring, and training formalised into a single platform. Built by engineers, for serious data teams.
The principles we operate by.
Quality over speed.
We don't rush deployments. A data platform built properly saves months of debugging later. We take the time to do it right.
Both sides must win.
If engineers aren't paid well and growing, the model fails. If companies don't get real value, it fails. We optimise for both — always.
No black boxes.
We document everything. We explain our decisions. When we leave, you should understand exactly what was built and why.
Production is the bar.
We don't train on toy datasets. We don't build proof-of-concepts that can't scale. Production quality is the minimum standard.
“To create a sustainable ecosystem where data engineers grow through real work, companies solve real data problems, and both sides win through trust, quality, and shared success.”
We're a small team doing serious work.
If you're a data engineer who wants to do meaningful work, or a company that wants a reliable partner — we'd love to talk.