Senior Data Engineer
Pubblicato il 03-10-2026 - HLPY in Siena
We're building the future of mobility.
At hlpy, we're building much more than a company.
We're building the technology platform that is transforming how mobility services are delivered across Europe.
Every month, our platform orchestrates tens of thousands of real-world operations, connecting drivers, insurers, fleets, OEMs, service providers and business partners through technology.
As we continue to expand internationally, broaden our product offering and integrate new businesses, the complexity of what we do grows with us.
Scaling hlpy isn't simply about increasing revenues.
It's about building an organization capable of executing consistently across countries, products and teams.
To get there, strategy alone isn't enough.
Execution is what makes the difference.
That's why we're looking for a genuinely senior, hands-on Data Engineer to join our AI & Data team as a peer to our current engineers — someone who owns definitions, not just deliverables.
Our analytics platform — dbt on Snowflake, fed by CDC replication from our operational PostgreSQL estate, by our ERP,
and by partner files and webhooks — is what tells hlpy and its enterprise customers what actually happened on every roadside assistance mission across four countries. Those numbers are not decoration: they settle SLAs, they drive invoices, and they land in our customers' inboxes every morning.
You will own models end to end, from raw source to the extraction files our contracts depend on, and you will be expected to push back when a number is wrong.
Key Responsibilities
1. Modelling & Ownership (dbt on Snowflake)
- Design, build and own models across the full stack — staging, intermediate, the entity-pure silver layer, marts, and the customer-facing outbound extractions — in a dbt project of roughly 200 models and growing.
- Build models that stand up to scrutiny. There are cases where the same business event is captured by more than one system, and the right answer is not obvious from the data alone: we