Makes your data AI-ready — pipelines, quality gates and retrieval foundations, because agents are only as good as what they can reach.
Reliable ETL/ELT into a warehouse your team and your agents can trust.
The retrieval layer for RAG — chunking strategy, refresh jobs, index hygiene.
Validation, deduplication and freshness checks — garbage stops before it reaches the model.
Ownership, lineage and access — the audit answers before the auditor asks.
CRM, support, billing, product events — unified instead of scattered across ten tools.
Storage and compute tuned so the data platform doesn't eat the AI budget.
Hired the week someone admits the RAG demo fails because the data is the problem — scattered, stale, duplicated and unowned.
Every data engineer on our bench has passed a role-specific battery — designed for the AI era, where the portfolio matters more than the years.
Messy multi-source data to unify — we score modeling choices and failure handling.
Hands-on, on real-shaped data. No whiteboard trivia.
How they caught bad data before it hit production — or what they changed after it did.
We ask what their last platform cost and what they'd cut. Good data engineers know.
Every placement starts with agreed outcomes. This is the typical shape for a data engineer — calibrated to your context in the intro call.
Audits sources, schemas and quality; the data map exists and the worst pipeline is stabilized.
Core pipelines rebuilt with tests and freshness checks; the warehouse becomes trustworthy.
Retrieval layer feeding AI features properly; lineage documented for the auditors.
Straight answers to what clients ask before the first placement — the rest is a 30-minute call.
If your data is scattered and unowned — often yes, or in parallel: AI features are only as good as retrieval, and retrieval is only as good as the pipelines behind it.
SQL and Python as the core; dbt, Airflow-class orchestration, the major warehouses and vector stores on top. Tooling follows your estate — the discipline is what's constant.
Classic CV screening barely works for roles this new — so we vet on artifacts and exercises instead: shipped work, live design or build tasks, and evaluation-writing. The battery is role-specific and documented, so you see exactly what was tested.
The first 60 days are the proof: if the match isn't right, the placement ends without long-term obligation — or we replace the profile. The risk of a wrong hire stays with us, not with you.
From our network across the Netherlands, Ukraine, Hungary, Romania, Poland and Bulgaria — CET ±1 and fluent English, so they join your standups live. Probegin contracts and payrolls them; you get one Dutch counterparty.
A 30-minute brief is all we need. Two to three vetted profiles follow — you interview, you choose.
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