Not every data professional started out writing SQL queries. Andreas Granqvist studied Accounting and Finance before finding his way into tech – a route that might look unusual on a CV but one that has shaped how he thinks about data to this day.
Now leading Teamit’s data capabilities, Andreas designs platforms, builds engineering practices, and has played a central role in shaping the company’s Ailandai offering. He works across the full data stack in cloud and on-prem environments, and has delivered solutions in manufacturing, finance, healthcare, and the public sector.
How did you become a data professional? Where did it all start?
– I’ve had an interest in technology for as long as I can remember. For a long time I was going back and forth between a career in business or tech. I studied Accounting and Finance first, which gave me a solid understanding of how organizations run and how financial data flows through a company. The pull towards technology was always there, so eventually I went on to study Computer Science and Information Systems too. That combination ended up shaping my whole career.
– It’s not the most typical background for someone in my role, but understanding both the business side and the technical side has been a real advantage. When I’m designing a data platform or working on an AI powered application, I’m not just thinking about how to make it work technically – I’m also thinking about the business needs and the ROI potential.
How has your career evolved over the years?
– I started as a consultant in 2017 with ERP implementations and financial reporting. Over time I drifted towards the deeper technical end – backend work, data platform design, ETL development. I kept wanting to understand what was happening behind the dashboards.
– I’ve worked across Microsoft, Azure, GCP, AWS and on-prem environments. That breadth matters – not everything lives in the cloud, and we’re now building agentic AI systems that run fully on-prem. When ChatGPT came out I was sceptical at first, but by 2024 I was convinced of what generative AI could actually do. I wanted to be part of that shift.
What do you like most about your work? What motivates you?
– What really motivates me is challenging myself and constantly learning new things. I get
restless if I’m doing the same thing for too long. And right now is a great time for that,
because in today’s fast-paced GenAI-centered world there’s no shortage of new things to
figure out. Every week there’s something new to try, some new way of doing things, and I
find that really energizing.
– I’ve worked with organizations in all kinds of industries and people with all kinds of
backgrounds. It’s always interesting to learn something new about a yet unfamiliar domain
and from people who think differently than I do. That never gets old.
What are you most proud of in your work?
– Building out Teamit’s data capabilities from the ground up – not just the technical work, but also the architecture, processes, and foundations for the team to build on. A lot of that is visible in our Ailandai offering, which covers GenAI and Agents, data platforms, governance, DevOps, and open source.
– What I’m most proud of is that we’ve built something real. Not just a service description on a website, but actual capabilities that deliver value to clients. Seeing the Ailandai offering solidify and expand is probably the most rewarding part of my career so far.
What challenges have you faced in your work?
– I’m a very hands-on person, which is mostly a strength but can also be a challenge. I quite
easily take on too many things and overextend myself if I’m not careful. When something
interesting comes up I want to be involved, I want to build it, and I want to understand it.
That’s great for learning and getting things done, but sometimes I have to remind myself that
I can’t do everything at once.
– It’s something I’ve gotten better at over the years, but it’s still a work in progress. Learning
to delegate and prioritize is just as important as the technical skills.
How do you develop your skills?
– Whenever I’m not spending time with my lovely family, working out, or playing my personal
curse, Dota 2, I try to stay on the pulse of where data and AI are heading. I spend a lot of
time picking up new tools and patterns. I also do a fair amount of recreational programming.
I tinker and explore new ideas, try out open-source tools, and build things just to see how
they work. It’s a hobby as much as professional development.
– Generative AI has been a big focus area lately. I’ve fully embraced it at this point and
nowadays I mainly rely on a number of terminal-based harnesses along with various skills,
scripts, and MCP to get things done. It fits well with how I like to work. At Teamit, we’ve also
organized GenAI training and certification for the team, which has been great for raising the
bar across the company.
How do Teamit’s values (attitude, trust, transparency, enthusiasm) show in your work?
– Transparency is a big one for me. Not just in the open-source sense, but being open to
new ideas and exploring new possibilities with an open mind. Teamit gives me the space for
that. Trust is something I feel every day too. I’ve been given the responsibility to shape our
entire data and AI practice, and you don’t get that without real trust in people. Attitude shows
in how we approach things. We do our best and we’re proud of the results, and I think that
comes through in what we’ve built. As for enthusiasm, I spend a fair amount of my free time
thinking about how to best manage the number of Linux machines I have at home in the
most efficient way and how to optimize my workflows. Pair that with hobby programming and
the enthusiasm for technology comes naturally.
Any plans for the future?
– I want to keep growing what we’ve built at Teamit, deepening our data and AI capabilities
so we can deliver even more value for our clients. On a personal level, I want to keep
broadening my cloud and platform expertise and push further into the AI space. Data,
engineering, and AI are all converging right now and it’s a really exciting time to be working
in this area.
– And I’ll keep tinkering. That’s never going to stop.
Andreas’s expertise spans cloud platforms (Azure, GCP, AWS) and on-prem environments, data
platforms, ETL/ELT pipelines, AI systems architecture, data-driven applications, full-stack
development, and DevOps. He is fluent in English, Finnish, and Swedish.
Read more about Teamit and check out our open positions: Career at Teamit