EuropeVisaJobs

Senior Data Engineer

SHIFTBASE B.V. · Zoetermeer, Netherlands

Confidence
Medium confidence
Posted
22 Oct 2026
First seen
24 Oct 2026
Last checked

Evidence

Medium confidence

SHIFTBASE B.V. is on the Dutch IND register. The posting doesn’t mention visas.

Sponsor register

Dutch IND public register of recognised sponsors

Listed as Shiftbase B.V.. KVK 59514701. Snapshot 26 Oct 2026.

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Job posting

Doesn’t mention visas or relocation.

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Still open

Seen on the job board

First seen 24 Oct 2026. We check every day and remove closed roles.

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Being on the register means SHIFTBASE B.V. can sponsor visas. It doesn’t confirm this role qualifies, so check with the recruiter.

About the role

Data Engineer Shiftbase is building the self-driving assistant for shift-based businesses across Europe. Our customers range from independent restaurants in Amsterdam to multi-location retailers in München, and they spend hours every week on scheduling, time tracking, payroll prep, and HR admin. We want to take that work off their plate and eventually do it for them.

Underneath that product vision sits a data challenge. Insight, automation, and AI all depend on data people can trust, and the foundation for it doesn't exist yet. You will build the foundation that fixes this. What you'll do • Architect the warehouse. Design and own our BigQuery and Dataform warehouse from the ground up.

Build a layered, well-modeled foundation, medallion staging through marts, not only the models that sit on top. Ask every day whether the whole company can trust and reuse it. • Make the data flow reliably. Build ELT and ETL with incremental, idempotent loads, orchestration, and retries, so pipelines run on time without anyone watching them. Ship monitored pipelines that hold up in production. • Take the transform layer. Own the Dataform model-building and transform layer, taking full responsibility for the transformation layer and freeing up capacity for semantic modeling and business definitions. This unblocks the whole team. • Build trust into the data. Make validation, freshness monitoring, alerting, and lineage the default. Diagnose failures at the root cause.

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