Senior Data Engineer

<h3><strong><span style="color:#121317">Data Engineer</span></strong></h3><p style="text-align:start;"><span style="color:#121317">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.</span></p><p style="text-align:start;"><span style="color:#121317">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. </span></p><p style="min-height: 1.7em;"></p><p style="text-align:start;"><em><span style="color:#121317">You will build the foundation that fixes this.</span></em></p><p style="min-height: 1.7em;"></p><h3><strong><span style="color:#121317">What you'll do</span></strong></h3><ul class="ak-ul"><li><p><strong><span style="color:#121317">Architect the warehouse.</span></strong><span style="color:#121317"> 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.</span></p></li><li><p><strong><span style="color:#121317">Make the data flow reliably.</span></strong><span style="color:#121317"> 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.</span></p></li><li><p><strong><span style="color:#121317">Take the transform layer.</span></strong><span style="color:#121317"> 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.</span></p></li><li><p><strong><span style="color:#121317">Build trust into the data.</span></strong><span style="color:#121317"> Make validation, freshness monitoring, alerting, and lineage the default. Diagnose failures at the root cause. leadscorev2 is the outcome this role exists to prevent.</span></p></li><li><p><strong><span style="color:#121317">Serve the whole company.</span></strong><span style="color:#121317"> Feed clean, governed datasets to Metabase, HubSpot, and the ML and AI work the product ML team owns. Push modeled data back into the tools business teams act on, including HubSpot and </span><a rel="noopener" target="_blank" href="http://Customer.io"><span style="color:#121317">Customer.io</span></a><span style="color:#121317">.</span></p></li><li><p><strong><span style="color:#121317">Own the Platform handshake.</span></strong><span style="color:#121317"> Run the day-to-day collaboration with the Platform team on our GCP foundation, a bridge that only gets part-time attention today.</span></p></li><li><p><strong><span style="color:#121317">Treat the warehouse like a product.</span></strong><span style="color:#121317"> Keep documentation, lineage, and discoverability current so departments trust the data assets, and handle sensitive HR and workforce data to GDPR standards.</span></p></li></ul><p style="min-height: 1.7em;"></p><h3><strong><span style="color:#121317">What success looks like in your first 3–6 months</span></strong></h3><ul class="ak-ul"><li><p><span style="color:#121317">The warehouse has a real foundation. The first vertical slice, our accounts model, ships with tests and monitoring.</span></p></li><li><p><span style="color:#121317">You fully own the Dataform transform layer, creating capacity for semantic modeling and business-definition work</span></p></li><li><p><span style="color:#121317">Pipelines run against a defined freshness SLA, and you catch breaks before stakeholders do.</span></p></li><li><p><span style="color:#121317">Documentation and lineage cover what you own, and datasets that were stuck now flow to the teams that need them.</span></p></li><li><p style="min-height: 1.7em;"></p></li></ul><h2 style="text-align:start;"></h2> <br> <h3><strong><span style="color:#121317">What we're looking for</span></strong></h3><p style="min-height: 1.7em;"></p><p style="text-align:start;"><span style="color:#121317">You have built warehouse foundations yourself. You designed them rather than maintaining someone else's, with a track record in:</span></p><p style="min-height: 1.7em;"></p><ul class="ak-ul"><li><p><span style="color:#121317">Designing layered warehouse architectures (medallion, bronze-silver-gold) and dimensional models (star and snowflake) that teams reuse</span></p></li><li><p><span style="color:#121317">Advanced SQL as your daily working language</span></p></li><li><p><span style="color:#121317">Hands-on BigQuery, since our stack is GCP</span></p></li><li><p><span style="color:#121317">Building a SQL transform layer in Dataform, or strong dbt experience.</span></p></li><li><p><span style="color:#121317">ELT and ETL with incremental, idempotent loads and real orchestration, scheduling, and dependency management</span></p></li><li><p><span style="color:#121317">Data quality, testing, freshness monitoring, and lineage built in from the start</span></p></li><li><p><span style="color:#121317">Python for pipeline code, scripting, automation, and API integration</span></p></li><li><p><span style="color:#121317">Reviewable, repeatable change through Git and PR-based deployment</span></p><p style="min-height: 1.7em;"></p></li></ul><p style="text-align:start;"><span style="color:#121317">Nice to have, not required: another modern cloud warehouse such as Snowflake or Redshift; managed ingestion such as Airbyte; preparing data for ML, LLM, and agentic use cases; and familiarity with B2B SaaS metrics and HR or workforce data. English is our working language, and Dutch is not required.</span></p><p style="min-height: 1.7em;"></p><p style="text-align:start;"><span style="color:#121317">This role isn't infrastructure engineering, ML or MLOps, or dashboard analysis. The Platform team owns infrastructure, the Product ML team owns ML, and the business teams own dashboards. It also isn't for someone who has only maintained a warehouse another person designed. You build the foundation properly, stay transparent about data quality and trade-offs, and treat the warehouse as a product for the whole company. You'll report to the Head of Operations and partner closely with the Platform team on the company's data architecture.</span></p><p>Find <a href="https://www.arbeitnow.nl">Jobs in Netherlands</a> on Arbeitnow</a>