Senior Analytics Engineer

If you’re the type of analytics engineer that prefers to have a list or backlog handed over, this is not the job for you.

But if you’re the type that wants a seat in the room where product decisions get made, you’ve come to the right place.

We’re looking for a Senior Analytics Engineer who wants to take the torch and show the way. Nobody here hands you a backlog. You decide what's worth measuring on a device that’s used by millions of drivers every day. That means that when our leadership asks whether the last release actually made anyone’s drive better or safer, the number they're looking at is one you defined.

You'd be the fifth person in our product data team, consisting of two data scientists, two data engineers, and soon (hopefully) you - all reporting to our Head of AI & Data. Small enough that everyone knows what everyone else is working on, big enough that you're not the only one losing sleep over a broken pipeline.

What you'll be doing Write and maintain the product-side dbt models, shared with the Commercial-side analytics engineer - tested, documented, reviewed like any other code

Own the product metric definitions and surface them through Steep

Keep pushing for one source of truth - reconciling definitions, retiring duplicates

Define and validate tracking for new features with PMs and engineers before they ship

Go deeper where self-service stops: post-launch evaluation, cross-feature trends, and the analysis nobody knew to ask for - and bring it into roadmap discussions early, not after the decision's made

Help choose and introduce a product analytics tool

Make our data reliably queryable by LLM tooling, and help figure out where agents actually save time versus just add noise - we're early here, deliberately, so there's real room to shape it

We imagine you're someone who Has owned product data models end to end - designed, in production, accountable when a number turned out wrong - and close enough to the business to argue about what the number means, not only how it's computed

Has strong data engineering fundamentals - pipelines, warehousing, dbt, advanced SQL and solid data modelling, comfortable in Snowflake and AWS

Can design event tracking, define the schema before it's built, then check it actually fires

Has worked hands-on with a product analytics platform

Writes working Python and takes data quality seriously

Enjoys working across disciplines - PMs, software and hardware engineers, designers, data engineers. Most of the good work here sits between teams, not inside one

Is curious and agentic, ideally has actually built something with LLMs, not just used one

Documents what they build, so the next person (or the next agent) can pick it up without you in the room

How is it working at OOONO? We're glad we asked. It's a nice working place. As in nice-nice. We have a relaxed, informal atmosphere and a flat hierarchy. Whenever you need a break from your important work stuff, you can get beat in table tennis, foosball, or just smalltalk about the weather by the coffee machine. We have monthly social events where we do anything from go-karting to going to festivals.

And when we're not social? Then we're pretty damn ambitious. We don't like conservative targets or linear growth. We're all about the extraordinary. This has led OOONO to become one of the fastest-growing tech scaleups and surprise-surprise: we have no plans of slowing down. It's a place to grow, thrive, and take the next step in your career.

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