Analytics Engineer

We are looking for a full-time Analytics Engineer in-house (m/f/d) to join our motivated global Insights team starting as soon as possible in the Stockholm or Munich office. 

 

The Role

As an Analytics Engineer, you’ll help shape how data is structured, accessed, and used across the business. You’ll work closely with stakeholders to build reliable, scalable data solutions that support smarter decisions.    As a vital member of our international IT organization, you will be involved in the foundation of our internal product development and will join the cross-functional data team that is responsible for developing and maintaining Netlight's business-critical data platform and strives to decentralize analytics. That is why it is important that you are a self-driven person, who is comfortable with taking initiative and responsibility, as well as a service-minded and communicative team player.   

Who you are

• A trusted communicator who builds relationships across technical and non-technical stakeholders and translates data into decisions

• Self-driven and proactive, but also team-oriented, with sound judgment on when to lean on AI tools for speed and when human oversight and design thinking matter more 

• Comfortable working in ambiguity — organized yet flexible, able to adapt as tools, priorities, and team structures evolve quickly 

• A curious, fast learner with a growth mindset — genuinely energized by new tools, AI-assisted workflows, and continuously raising your own technical bar 

Qualifications

• Based in Stockholm or Munich 

• A degree in a quantitative field (e.g. software engineering, computer science, economics, mathematics, statistics) — if you think you’re a great fit, we want to hear from you! 

• At least 2+ years of relevant experience in fields like Analytics Engineering, Data Engineering, Data Analytics, Data Science, or Software Development.  

• Strong SQL skills, with hands-on experience building and testing data models in dbt on a cloud warehouse, and an understanding of dimensional data modeling (star schemas, facts and dimensions) 

• Solid grasp of version control with Git, including CI/CD workflows for data pipelines 

• Familiarity with Python for data transformation, automation, and light pipeline work 

• Fluent in written and spoken English (business level) 

• Comfort working with AI copilots and AI-assisted analytics tools (e.g. Copilot-style code/doc generation, AI BI assistants) while maintaining human oversight on data quality and design