Operating across Europe and Asia, We Maintain specialises in the maintenance and modernisation of lifts, escalators, automatic doors and fire safety systems, combining hands‑on technical expertise with technology and data. Our approach is built on a simple belief: maintenance can be more reliable, transparent and effective when teams have the right tools, the autonomy to make decisions and a clear understanding of what's happening across the equipment they look after. Since 2026, Otis has been our majority shareholder. We Maintain continues to operate independently, retaining its own organisation and culture while benefiting from additional resources to support our growth. Three core values guide the way we work every day: Care (looking after others): treating colleagues and customers with respect, consideration and a genuine sense of responsibility. Grit (determination): seeing things through with high standards, commitment and perseverance. Uniqueness (being different): embracing different perspectives, fresh ideas and new ways of doing things. Our ambition is to raise the standards of maintenance, alongside the people who make it happen every day. Because here, you don't have to choose between impact and stability. Large groups often offer stability, but little room to manoeuvre. Smaller organisations allow more freedom, but sometimes without clear direction. At We Maintain, we strike the right balance: Real autonomy, with modern tools and strong support A culture built on trust, transparency and respect Genuine opportunities for growth and internal mobility A team that values commitment, perseverance and the drive to make things happen And our values guide us every day: Care : Working with respect and kindness, internally as well as with our customers Grit : Seeing things through, with high standards and determination Uniqueness : Daring to be yourself, sharing your ideas and challenging the status quo Who we’re looking for We are looking for a Lead Analytics Engineer to be the right hand of our CTO on data, and the right hand of our Global Head of Operations on making a 350-person, four-country operation data-driven. It is one job made of two halves. If what you want is to go deep on modelling and be left alone, this is not the role. Roughly half of it is sitting with Operations, in the UK, France, Singapore and Hong Kong, arguing about what we should be measuring and why, and then being the person who makes that measurable. We're not starting from scratch. There's a data lake, dbt on Big Query, Looker on top, and it works. Software engineers, Data scientist and even some business champions commit to it daily. Nobody owns all of it though, which is where you come in. This is a hands‑on individual contributor role with no direct reports. You will not manage a team, and we are not planning to build one under you. You will set the standard for how data lands in our lake and how it gets used, and hold the rest of the engineering team to it. You’ll join a Product & Engineering team of around 20 people, growing by 50% over the next year. Your day-to-day at We Maintain As Lead Analytics Engineer, You Will Bring new data into the lake, constantly. This is the steady heartbeat of the role:



new sources, new fields from sources we already have, new needs from every part of the business. None of it is rocket science, but our business is a dense one. Four countries, thousands of buildings, an Io T fleet, field engineers, contracts, regulation. Modeling it well is the hard part. Own the modeling layer. dbt on Big Query today: models, tests, documentation, reliability. You decide how it evolves, including whether dbt is still the right answer in two years, or when the Io T fleet has grown tenfold. Define what “good” looks like for our operational KPIs. Our field and operations teams know their business better than anyone. What they don't have is someone technical standing next to them, turning that knowledge into numbers everyone trusts. You'll be that person, with Marine, our Global Head of Operations, as your closest counterpart: deciding what we count, how we count it, and what a result has to show before it means we’re winning. Help one standard become true in four countries. We operate in the UK, France, Singapore and Hong Kong, and good practice invented in one of them should become how the whole group works. Spotting it and rolling it out is Operations’ call. Making sure it’s made on evidence rather than instinct, and that we can tell afterwards whether it worked, is yours. Build the analysis the business doesn’t have yet: client churn prediction, contract-level economics, engineer productivity, and what our Io T devices tell us about how lifts are actually used. Keep the platform fast and affordable. Big Query cost control is your call, not an afterthought. Extend the platform where it needs extending: UDFs, signed links, LLMs running directly in the warehouse, and whatever else the next problem needs. Raise the standard around you. Engineers across the team push data into the lake. You set the rules of the road, and you push back when they’re not followed. On AI, specifically Use them. Obviously. We’d think it strange if you didn’t. The tooling has moved the goalposts in the last two years, for how we ship and for what we can ship at all. We’d rather talk about what that makes possible than about which model we’re on this month. It doesn’t remove the need for strong engineers. It makes them more valuable, because someone still has to know what good looks like. Use it however you see fit. You will not be BS’d or FOMO’d about it here. And a word on the field From the outside the industry looks remote and a bit dull. It’s neither, and what you find once you’re in it is how tightly coupled everything has to be. Problem detection feeds the device state service, which needs the SLA on the contract, which depends on the customer, and which regulation reads differently in each of our four countries. Very little here is a self‑contained feature.



The data you will provide will change how someone’s day goes on site. You’ll see that for yourself during onboarding. It isn’t a day‑to‑day part of the job, but it’s the reason the job matters. What we’re looking for You Might Be a Great Fit If You Have been the person who owned a data platform end to end, from ingestion through to the numbers a leadership team argues over. Ideally without a large team behind you. Have done both halves. You’ve written the pipeline and you’ve sat in the room where the business decided what to do about the result. Neither one feels like someone else’s job to you. Are fluent in SQL, data lakes, transformation and ETL. We care much less about which tools you learned them in. Are comfortable being the standard‑bearer without the authority. Influence and credibility, not a reporting line. Can tell an operator they’re measuring the wrong thing and be listened to, because you understood their problem first. Bring structure to messy operational data and are not upset when reality refuses to be clean. Are at ease working fully remotely across four countries and two continents, and take the initiative to stay close to people. We do not require experience with our specific stack. If you’ve never touched dbt, Big Query or Looker but you’ve built and owned the equivalent elsewhere, we want to talk to you. English is the working language of this role. You’ve started, run or helped build something of your own, and you judge your work by what it changed rather than the code you wrote. You’ve worked in an operations‑heavy business: field service, logistics, industrial, energy, anywhere the data describes physical things happening in the world. You’ve worked with Io T or time‑series data. You have hands‑on experience with dbt, Big Query or Looker. You’ve introduced AI tooling into a data team in a way that stuck. You’ve worked across multiple countries and know how differently the same process can look in each one. We don’t expect you to have seen everything already. We do expect you to ramp fast and take ownership quickly. Why this role is different You’d own the data layer of a company that is currently working out how it wants to run globally. Most of the big questions haven’t been answered yet, and you’d be in the room for them. Senior data people usually end up either close to the warehouse or close to the business. Here it’s both, with a direct line to the CTO and to the General Head of Operations. And it’s full remote, properly. The whole team gets together in person three times a year. At We Maintain, we value diversity, encourage personal development, and are committed to inclusion. Whatever your background, story or identity, you are welcome to apply. As this is a Europe‑wide role, compensation is adapted to the candidate’s country of location and aligned with local market benchmarks. €80,000 – €105,000 base salary, depending on your country. The exact package will depend on experience, level of ownership, and demonstrated impact. We’ll confirm the specific range for your country before your first interview. #J-18808-Ljbffr

📌 Lead Analytics Engineer (F/M/X) (Madrid)
🏢 WeMaintain
📍 Madrid