Analytics Engineer; in-house

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.

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.

• 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

• Based in Stockholm or Munich

• A degree in a quantitative field (e.software engineering, computer science, economics, mathematics, statistics) — if you thinkyou’rea 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 indbton a cloud warehouse, and an understanding of dimensional data modeling (star schemas,factsand 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) whilemaintaininghuman oversight on data quality and design

• Bonus:
  
  Experience with, or strong interest in, semantic layers and metric governance — ensuring a single, trusted definition of key business metrics that both humans and AI tools can rely on

As an Analytics Engineer,you’llhelp shape how data is structured, accessed, and used across the business.

You’llwork closely with stakeholders to build reliable, scalable data solutions that support smarter decisions.

• Transform raw data into clean, usable datasets for analytics and business intelligence, and AIuse cases.

• Collaborate with stakeholders to define andmaintaina semantic layer andsingle sourceof truth for keybusinessmetrics.

• Ensure data quality and consistency across teams and tools.

• Build and maintain robust, well-documented data models using Snowflake and dbt.

• Provide compliant, user-friendly access to data across various tools (e.g.Power BI, Excel, or AI-powered BI assistants).

• Empower users of all technical levels — including AI agents — to find, understand, and securely query the data they need.

• Own the data access lifecycle end-to-end, balancing self-service efficiency with security, privacy, and compliance requirements.

• Maintain clear documentation and metadata (data catalog, definitions,lineage,ownership) so both people and AI tools can…