Distribusion is the world’s leading ground transportation marketplace and gives travellers seamless access to ground transportation online, from search to ticket purchase. We have built a cutting-edge B2B technology platform that connects bus, rail, and ferry operators in over 70 countries with the largest online retailers, including Google Maps and Booking.com.

We are shaping the future of travel and building the largest global network of transport providers and retailers. We are one of the fastest-growing startups in the travel industry, backed by leading venture capital investors including TQ Ventures, Lightrock, Creandum, and Northzone, and are headquartered in Berlin, Germany. Following our recent $80m Series C funding, we are ready to push beyond.

We're looking for an experienced Analytics Engineer to own our Data Build Tool project and semantic layer end-to-end. You'll join our Data Platform team and work directly with our data engineers, an analytics engineer, and stakeholders across the business. Your work reaches internal users and external data products that serve millions of travellers.

What you will do:

Own and evolve our DBT project: model design, incremental strategies, testing, documentation, and the semantic / reporting layer that serves the business.
Raise the bar on data quality. Build tests, contracts, freshness checks, and monitoring so problems are caught by the pipeline, not by a stakeholder in a meeting.
Own metadata and lineage. Make it easy for engineers and stakeholders to find what exists, understand where it comes from, and judge whether they can rely on it.
Improve the development process around dbt: CI, PR review, local testing, release workflow. The tooling should stay out of the way of the work.
Partner with stakeholders. Translate fuzzy questions into concrete requirements, challenge them when they need sharpening, and close the loop once the work lands.
Build reports when they're needed, but invest just as much in the models and semantic layer that make future reports cheap. Move the team towards self-service where it makes sense.
Push the team forward on tooling and process. As the data stack evolves, bring new ideas in - AI-assisted development, better testing patterns, improved self-service - and help the team adopt what's worth adopting.

Analytics Engineer (all genders)