How to hire data engineers in the EU without a 6-month search
Why narrow focus, practitioner-led assessment, and realistic salary bands beat generic IT recruiting for data roles.
The bottleneck is rarely sourcing
Data engineer searches stall when the role profile is vague, the salary band won't close in-market, or interviews can't distinguish pipeline builders from dashboard tweakers.
Define the bar before you open the req
Write down:
- Stack (dbt? Spark? Airflow?) and ownership scope
- Seniority signals that matter for your team
- Salary band you've validated against comparable roles
If the band won't close, fix that first — adding recruiters won't help.
Assess competence, not buzzwords
Practitioner-led technical interviews on real-world problems surface red flags CVs hide. We run the same assessments on our own delivery hires.
Speed comes from focus
Specialist recruiters maintain warm pools in data & AI. Generalists restart from zero on every search.
Takeaway
Hire faster by narrowing the role, validating budget, and assessing skills with people who build data systems daily.
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