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.
Korte og præcise svar på de spørgsmål, kunderne stiller inden den første ansættelse — resten klares i et 30-minutters opkald.
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.
Traditionel gennemgang af CV’er fungerer stort set ikke for så nye stillinger — derfor vurderer vi i stedet på baggrund af konkrete resultater og praktiske opgaver: færdiggjorte projekter, konkrete design- eller udviklingsopgaver samt udarbejdelse af evalueringer. Testforløbet er stillingsspecifikt og dokumenteret, så du kan se præcis, hvad der er blevet testet.
De første 60 dage er beviset: Hvis det ikke er det rigtige match, afsluttes ansættelsen uden nogen langsigtet forpligtelse — eller også udskifter vi profilen. Risikoen ved en forkert ansættelse påhviler os, ikke jer.
Fra vores netværk i Nederlandene, Ukraine, Ungarn, Rumænien, Polen og Bulgarien — CET ±1 og flydende engelsk, så de kan deltage live i jeres standup-møder. Probegin indgår kontrakter med dem og står for lønudbetalingerne; I har én nederlandsk samarbejdspartner.
Et 30-minutters briefing er alt, hvad vi har brug for. Derefter får du to til tre nøje udvalgte profiler — du afholder samtaler, og du vælger.
Book et introduktionsmøde