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Staff Data Engineer

Pubblicato il 10-10-2026 - Traveltechessentialist in Milano

ABOUT WEROAD: CONNECTING PEOPLE, CULTURES, AND STORIES
Founded in 2017, WeRoad is a fast-growing startup that is disrupting the travel industry in Italy, Spain, UK, Germany, France, Switzerland and… the USA
With 200 team members and 4K+ Travel Coordinators, we're a community of travelers who turn every trip into a life-changing experience. We connect like-minded millennials and send them on adventures to 1000+ destinations worldwide.
We're on a mission to design and deliver experiences worth living and sharing, through rewriting the rules of the travel industry.
Sounds exciting? Before you apply, please read through our Cultural Manifesto
ABOUT THE ROLE
JOB TITLE: Staff/Lead Data Engineer
LOCATION: Full Remote or Hybrid (Milan).
TYPE OF CONTRACT: Permanent, full-time
SALARY RANGE: €60,000 – €75,000
As Data Engineering Staff/Lead, you'll be a hands‑on leader — you'll write code, review architecture, and work shoulder-to-shoulder with a small, senior Data Engineering team (1–2 engineers) on the evolution of WeRoad's data architecture: the BigQuery warehouse,



the dbt transformation and semantic layers, and the pipelines that turn raw data into trusted, self‑service insight across every market. You'll report to the Director of Data Engineering & AI and work hand in hand with the wider Data & BI team, Product, and business stakeholders.
It's a small, high‑leverage team, so this is a player‑coach role by design: you'll set the technical direction, standards, and roadmap, but you'll also be in the code and in the pipelines yourself whenever it counts. You'll take our data platform from solid foundations to best‑in‑class: a restructured warehouse and semantic layer, near‑real‑time serverless ingestion, dashboards‑as‑code, and AI woven through both how we build and what we ship.
What you'll do:
- Lead our Data Engineering team (1–2 engineers) — owning delivery, quality, and career development.
- Own and evolve WeRoad's data architecture: the layered BigQuery warehouse (raw →

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