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
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
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
What you will do
Transform raw data into clean, usable datasets for analytics and business intelligence, and AI use cases.
Collaborate with stakeholders to define and maintain a semantic layer and single source of truth for key business metrics.
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 trust and correctly interpret the data
Continuously evaluate and improve data models for performance and scalability.
Contribute to agile ways of working, participating in planning, refinement, and delivery cycles.
Stay current with emerging tools and practices in the data stack (e.g. orchestration, observability, AI-assisted development) and help the team adopt what's genuinely useful.
Data Modeling & Quality
Governance & Enablement
Optimization & Agile Delivery
What we offer
- The possibility to be a core part of one of the most successful IT-consultancy companies in the industry - and contribute to the continued growth of our thriving Stockholm office.
- Professional development and long-term career progression through knowledge sharing, mentorship, feedback, coaching, and external training
- Modern and centrally located offices in Stockholm or Munich
- A culture centered around community, collaboration, and continuous learning, complemented by social and competence-building events
- Everything you need to do your magic (computer, phone, mobile subscription)
- Mental health & parental support offerings
- 30 days of paid vacation.
- Deutschlandticket
- Wellpass
- 5000 sek / year in health care benefit (“friskvård”)
- Private pension savings
Skills Required
- Degree in a quantitative field such as software engineering, computer science, economics, mathematics, or statistics
- At least 2 years of relevant experience in analytics engineering, data engineering, data analytics, data science, or software development
- Strong SQL skills
- Hands-on experience building and testing data models in dbt on a cloud warehouse
- Understanding of dimensional data modeling, including star schemas, facts, and dimensions
- Experience with Git version control and CI/CD workflows for data pipelines
- Familiarity with Python for data transformation, automation, and light pipeline work
- Fluent written and spoken English at business level
- Comfort working with AI copilots and AI-assisted analytics tools while maintaining human oversight
- Experience with or strong interest in semantic layers and metric governance
What We Do
Netlight is a relationship organisation of 2 000 consultants making aspiring digital leaders successful. Providing a full range of consultancy services from technology and design to data and management. Netlight has been awarded top employer several times, as well as for growth, continued profitability, and engagement for equality and diversity within the IT industry. Located in Stockholm, Oslo, Helsinki, Copenhagen, Munich, Hamburg, Berlin, Frankfurt, Zurich, Cologne and Amsterdam. We refine the concept of IT consulting to be about talents who, in cooperation, create valuable results for our clients. For our consultants, the client's interest always comes first. Our clients are market-leading within their field. Our goal is to deliver independent solutions and tangible results based on our clients’ conditions and business objectives. We accomplish this by focusing on competence, creativity and business sense. Our offering is realized by Netlight’s talented consultants, with qualifications above the ordinary. Netlight delivers independent solutions together and benefits from our collective expertise, beyond the single individual’s ability. This allows Netlight to engage where technology is business critical by taking on our clients’ biggest challenges and identifying opportunities or solving problems. We call it to grow talent, create together and engage in challenge









