Help Us Build The Future of Travel At Airalo, we're making it easier for people to stay connected wherever they travel. As the world's first eSIM store, we help millions of

Help Us Build The Future of Travel
At Airalo, we're making it easier for people to stay connected wherever they travel. As the world's first eSIM store, we help millions of travelers access affordable mobile data in 200+ countries and regions around the world.
Today, we're a team of 400+ people across 60+ countries, building a product used by travelers every day. We've grown quickly, but we've worked hard to keep what matters: trust, ownership, and the freedom for people to do great work without unnecessary layers or bureaucracy.
We're fully remote by design, genuinely global, and united by a shared mission to make travel simpler for everyone.
Your Next Destination
Location: Remote, anywhere in Spain or the UK.
Contract:
Spain: Full-time, permanent contrato indefinido via Deel (our employer of record in Spain)
UK: Full-time, permanent
Benefits: Learn more about our benefits here in this link - https://airalo-public.notion.site/Benefits-25396a97ffca81fb9bc1f0be479f1be3?pvs=74
Languages: English is our main working language day to day, so you'll need to be comfortable communicating in it both in meetings and async.

We're looking for an Analytics Engineering Manager to lead our self-service analytics infrastructure and data modeling practice at Airalo. You'll own the foundations that make analytics possible at scale: the semantic layer, core data models, dashboards, and the self-service platform (Lightdash) that enables teams across the business to answer their own questions. This is a building role-you'll establish how we model data, how we govern metrics, and how we roll out self-service capabilities across a 20M+ user business operating in 190+ countries.

You'll report to the Director of Data and partner closely with analytics teams and stakeholders across the business, translating their analytical needs into scalable, production-quality data models. Success looks like business users confidently answering their own questions, a governed semantic layer that analytics teams trust, and a self-service platform that replaces our patchwork of legacy reporting tools and robust data models that scale without use cases.