Curious, cool, and a little nerdy – getting the lowdown on Analytics Engineering at Wolt

At Wolt, analytics engineers help turn massive amounts of data into clear, usable insights for the business.

This team sits between raw data and the people who need to use it. They clean it up, structure it, build the metrics, and make sure the business has something clear and reliable to work with. Or, as Essi puts it with a smile, they’re kind of “data janitors”, keeping things clean so everyone else can do their jobs better.

Meet Alexis Oddos Attia, Essi Grönroos, Julia Luzganova, and Sami Sutinen: four analytics engineers based in Germany and Finland.

Four backgrounds, same destination

Alexis is the newbie of the group. He joined Wolt about eight months ago, is based in Germany, and works with Wolt’s biggest merchants. Before Wolt, he spent around seven years in the field and brought with him both a business and a computer science degree.

Essi and Sami both joined Wolt as interns and have grown with the company over the years. “Analytics engineering didn’t exist at the time I joined 6-7 years ago, and I’ve been in a number of different teams in the company. Currently I’m the data lead for the Wolt Market team, based in Finland”, says Essi. Sami has been with Wolt for five years and he is a Senior Analytics Engineer in finance. “What really enticed me to join was the fast growth and buzz around Wolt that has stayed with it to this day”, he shares.

Julia joined two years ago. “I started my career as a data engineer. I enjoyed it, but I was really missing the connection to the business and how my work impacts decisions”, Julia explains. Analytics engineering allowed her to stay close to the technical side while also connected to business decisions.

Analytics engineering or… data janitors?!

For someone outside the industry, or possibly even inside, let’s get to the one question you’re probably wondering at this stage: what distinguishes an analytics engineer from a data engineer or data scientist?

Analytics engineering sits between data engineering and data science. It focuses on structuring, cleaning, and modelling data so it can be used across the business.

Data engineers bring raw data into the platform, but it still arrives unstructured. Analytics engineers take that data, clean it up, structure it, and then connect it with the business. The data scientists then leverage that data to build analysis to help inform better decisions.

“Analytics engineering is building the data structure that data scientists will use to build analysis and experimentation, so we're upstream compared to them,” Alexis says, noting that data scientists in Wolt could also be understood as data analysts in other companies.

At Wolt, analytics engineers build the metrics and data infrastructure the business relies on every day. They act as a bridge between data engineering and data science. In other companies, some of the work might sit under data analysis, but here the role is its own thing.

“It was only established a few years ago, we try to follow strong engineering practices but with real business value.” Julia says.

Essi sums it up in a way that is both funny and surprisingly accurate:

“When anyone asks me what I do for work, I say I'm a data janitor, because I think that describes it perfectly. We keep things clean for everybody else.”

Day in the life of an Analytics Engineer

While the roles are similar in nature, the day-to-day work looks quite different depending on where you sit in the business.

Sami, for example, works in the finance domain, focusing on Wolt’s profitability. His work starts with unstructured data, different cost streams, revenue streams, and transaction-level details, and turns it into something the business can use.

The goal is simple: understand where we’re bringing in money and where we can improve.

“We want to structure the data so that we can make sense of it for the business. So they can say: these orders are making money, and these are the levers we can pull,” Sami explains. 

Julia, on the other hand, works in the consumer domain. Her work sits at the intersection of technical implementation and business collaboration, building data models and visualizations, but also working closely with stakeholders to define what should even be measured in the first place. Sometimes that means stepping back before building anything at all.

“From time to time, my task is not just about data, it’s about reframing the problem,” she says. 

For example, the business wanted a dashboard, but we didn’t know what we wanted to track yet. So instead of jumping straight into building, Julia helped organize a workshop to clarify goals, making sure the team was solving the right problem.

Alexis works closely with Wolt’s largest merchants, the enterprise accounts. His role often starts with identifying a business need, translating it into a technical problem, and then building a solution that can be used across teams.

“I’m working a lot with account managers, trying to understand their needs, framing the problem, designing it, and then quality-assuring it with others,” he says.

He also uses the same infrastructure to run analyses himself, connecting the technical and analytical sides of the role.

Essi works closely with the business and product teams. For her, the most important part of the job is building the right thing.

“If you just give people exactly what they ask for, oftentimes it ends up not being what they actually need,” she says.

Instead, the real skill is understanding the intention behind a request, stepping into the stakeholder’s shoes and figuring out what problem they are really trying to solve.

Across all four roles, the goal is clarity, helping teams make better decisions. “We make sense out of a lot of things, and internally this helps all teams understand what they're doing and make better decisions,” Alexis adds. And that impact reaches merchants, courier partners, and customers.

What’s it like to work here? “Low ego” and a drive to succeed

The team highlights two things: low hierarchy and balance.

“We have Friday games with consumer analytics engineers. We also talk about movies and fun facts, what happens during the week. This helps me both manage and enjoy my work,” Julia says. 

“‘Low ego’ is something that you hear a lot of people talk about here, and I think it’s definitely true. But people are still very much motivated, and there's a driven atmosphere within the company. I really value this,” Sami says.

Wolt also has a flexible approach to working at home or in the office, and Alexis found that after his experience in the banking industry coming into the office could actually be a positive thing.

“I’ve started coming to the office four times a week when I don’t have to come at all, which is a good sign! I really like coming to the office, having this good atmosphere here. We're getting lunch together every day,” he says.

Alexis noted the career opportunities, both vertical and horizontal, in a company of Wolt’s size were also a big plus, but said in some areas he had to draw a clear line and just say no.

“Sami tried to get me into ice swimming, but I refused,” he laughs.

Are you a future analytics engineer?

If there’s one thing the team agrees on, it’s that you don’t need to have everything figured out on day one.

What matters more is how you approach problems. Curiosity comes up again and again. The role isn’t just about writing queries or building models, it’s about asking the right questions and understanding how your work connects to the bigger picture.

“Technical skills are important, of course, but you can learn them on the way. If you look at the whole team, there's really different backgrounds because – at least when I started my studies – there wasn’t even a degree to become an analytics engineer. Some people from the team started as a chef! What’s more important is having the curiosity and business understanding: You need to think to yourself, how is what I’m doing impacting things beyond the code I see?” Essi says.

Attention to detail also matters. The systems analytics engineers build are used across the company, so small mistakes can have big consequences.

“You need to be quite thorough in what you’re doing,” Alexis says. “We’re maintaining a lot of data pipelines that can break, so it’s very detail-oriented.”

At the core, it’s about understanding how everything connects..

“You need to be a bit of a nerd sometimes. I mean, I would say we're all nerds in some way, nerds that understand the business and like to understand how everything is linked together. That would be a good definition of an analytics engineer. Oh, and quite cool – everyone here is a cool person!” Alexis says.

That balance between technical thinking and business context is what makes the role unique. 

Are you a curious, detail-oriented nerd who enjoys making sense of complex data? 🙂 Wolt is hiring! Explore analytics engineering and data roles at Wolt to see where your skills could take you! 🚀