Senior Data Analyst- 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 spent the past 6-months building the data platform: BigQuery, dbt and Lightdash. It's live and the company runs on it. What we don't have yet is the layer between that platform and the people who need to use it.
Right now, most teams still have to come to us. That's the constraint. The job is to close it, in two directions at once: build the things in Lightdash that let support, marketing, product, commercial and finance answer their own questions, and do the deep analytical work that nobody in those teams could do for themselves.
You'd be the most senior analyst here, working across the whole business rather than inside one function.
The team
Four people, reporting to the Head of Data. A data engineer on the platform, an analytics engineer on the model layer and the definitions behind Lightdash, and you on everything the business actually touches. Natlink is around a hundred people and backed by Verdane, so the data function is small, visible and expected to matter.
What you'll work on
Making teams self-sufficient. This is the larger half of the job.
Deep analysis nobody else can do.
The data
Most analyst roles offer clicks and transactions. You get those, and a good deal more.
Continuous positioning telemetry from devices working in real terrain. Behaviour from groups coordinating together rather than individuals using an app alone. Hardware and subscription revenue inside a single customer relationship. Trail camera data from remote sites. Emergency response data where the outcome variable is how quickly someone reached a person in cardiac arrest. Support and marketing across several markets with different cultures, seasons and regulations, and demand that swings hard enough each year to break most off-the-shelf models.
It's an unusually varied set for a company this size, and very little of it has been properly analysed. That's the opportunity.
What you'd grow into
Raising the analytical standard as the team grows. The formal data literacy work across the company sits with the Head of Data for now, and you'd take an increasing share of it over time as the self-serve foundation you're building makes it possible.
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
Nice to have
You'll fit if
You'd rather answer five questions that change a decision than close fifty that don't, and you can tell which is which before you start. You'd rather teach ten people to pull the number themselves than be the one they depend on, and you get something out of watching someone find their own answer. You go looking for the question instead of waiting to be handed one. You say the uncomfortable thing early, when it's still cheap, and you're happy to be wrong in public if it gets us to the right answer faster.
You probably won't if
You want to work from the data and not from the people. Half of this job is in conversation with teams who don't think in tables, and if that reads as an interruption to the real work, it isn't the role. Or you need a groomed backlog and precedent to work from: most of this is still unwritten, and you'd be the one writing it. Or you'd rather go deep in one domain than move across product, hardware, marketing, support and finance.
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.
