Analytics Engineer

Analytics Engineer- Join Our Growing Team!

Location: Stockholm or Remote Sweden

Natlink builds technology for coordination and response. A hunting team spread across several kilometres of forest. A dog working a scent line out of sight of its handler. Someone collapsing from cardiac arrest in a Swedish town, and the nearest trained volunteer needing to reach them before the ambulance can.

Underneath, it's the same problem: get the right people to the right place quickly, usually outdoors, often where the network barely works. Our services are used by close to a million Europeans, through WeHunt, Tracker GPS devices, Burrel cameras and Heartrunner.

Why this role exists

We can land data faster than we can model it. That gap is the biggest constraint on the company right now, and closing it is the job.

You'd own the layer between raw data and the models people use every day: the dbt project on BigQuery, and the definitions and semantic layer behind Lightdash. The measure is straightforward. How much well-modelled, trustworthy data is available to the organisation, and how quickly a new domain gets there.

You would not own ingestion, orchestration or infrastructure. That sits with someone else, deliberately. This role is modelling and the people it serves.

The team

Four people, reporting to the Head of Data. A senior data engineer on the platform, systems and pipelines, a senior analyst on analysis and stakeholder work, and you on the model layer between them. Natlink is around a hundred people and backed by Verdane, so the data function is small, visible and expected to matter.

Who you'll work with

Support wants to know which customers are about to give up before they write in. Marketing wants attribution across several markets with different seasons. Finance wants revenue that ties out across hardware and subscription. Product wants to know what people do in the field, not just what they tap in the app.

Every one of those is a modelling problem first. The hard part is working out what marketing actually means by an active customer, and getting finance and support to agree. That conversation is most of this job.

There's also a genuinely interesting structural problem in front of us: multiple products, several business models, and an emergency response platform joining a consumer hardware and subscription business. Working out how that fits into one model is something we'll do together, and you'll be in the room for it from your first month.

What you'll work on

• The dbt project on BigQuery: structure, layering, testing, performance
• The definitions and semantic layer that support, marketing, product, commercial and finance rely on daily
• Delivery speed, so a new domain gets properly modelled in days rather than weeks
• Over time, the standards and review process that keep it coherent, including for engineering teams contributing to the platform

What you'd grow into

This is a role with obvious room above it. Within a year or two we'd expect you to be setting the modelling standards rather than inheriting them, making the architecture calls yourself, and extending the model layer beyond analytics into operational and agent workloads. The Verdane portfolio is full of data teams solving the same problems, and you'd have access to that network.

How we work

Priorities are set with the leadership team through our data steering group, led by the Head of Data. You work on what the company has agreed matters, and you're expected to argue when you think it has that wrong. This is not a ticket queue.

Numbers that leave the building come from the data platform, not from source systems. We don't publish figures we can't reconcile or trust.

We're deliberately AI native. Claude Code and Cursor daily, conventions files in every repo, agents and automated flows in production. It's why a team this size can support a company this size. What matters is how you review and challenge what an agent produces, not how fast you can generate something.

What you need on day one

• dbt in production, where you owned models other people depended on
• Strong SQL and warehouse fundamentals, on BigQuery or something comparable
• Git and CI as your normal way of working rather than something you were asked to adopt
• You already work with AI coding agents every day

Three to five years is roughly the shape, but we care more about what you've owned than how long you've been doing it.

What you'll build here, and don't need already

• Ownership of a semantic or metrics layer that non-technical people genuinely use
• Setting standards other teams follow, and holding them when someone wants an exception
• Modelling across several products and business models at once

Nice to have

• Experience from a company where the data team was small and the standards were yours to set
• Swedish, Finnish or Norwegian

You'll fit if

You think the hard part is agreeing the definition, not writing the SQL. You'd rather put a rough standard on the table this week and have it torn apart than circulate a perfect one next month. You treat ambiguity as yours to resolve, not something to escalate. And you'd rather teach ten people to pull the number themselves than be the one they depend on.

You probably won't if

You want pipelines, ingestion and infrastructure in your remit. That sits elsewhere. Or you'd rather work from the repo than spend half your week with support and marketing, learning how they actually think.

How we hire

A first conversation with the Head of Data, followed by a short online psychometric and personality assessment you can complete from home in your own time. After that comes an interview with the team, and a working session where we hand you a real modelling problem and spend an hour on it together. You'll get the material shortly beforehand, not days in advance, and you're encouraged to use Claude, Cursor or whatever you normally work with. No take-home assignment. We'd rather see how you think than ask you about it. The assessments aren't pass/fail. They give us a starting point for the conversations, and we'll walk you through your results either way.

To apply:

https://natlink.careers.haileyhr.app/