Analytics Engineer

ABOUT THE COMPANY Join a team driving data strategy for one of Europe's largest software groups, working on platforms like VSIL (Visma Shared Intelligence Layer) and Visma Data Foundation — with real investment in making AI a first-class part of how the data organization operates, not an afterthought. ABOUT THE ROLE We're looking for an Analytics Engineer to join our Group Data & Analytics team and help shape how data gets modeled, tested, and delivered across Visma. You'll work hands-on across the full analytics stack — from modelling and transformation to dashboards and stakeholder-facing analysis — turning raw, Group-wide data into trusted, well-governed models that power decision-making across the organisation. This is an AI-heavy role: you'll be expected to use AI tools as a core part of your daily workflow — not just for writing SQL faster, but for documentation, testing, code review, data modeling design discussions, and increasingly, building AI-assisted or agentic data workflows. We want someone who's genuinely curious about how AI changes the way analytics engineering gets done, with a habit of experimenting and bringing learnings back to the team — not just someone who tolerates it. WHAT'S IT ALL ABOUT? Data modelling and transformation Design, build, and maintain robust dimensional data models and transformation pipelines using SQL and dbt in BigQuery Profile, clean, and verify data before publishing; write and maintain dbt tests to guarantee quality Contribute to the design and adoption of a semantic/metrics layer for consistent, governed self-service analytics Monitor pipeline observability and alerts, troubleshoot failures, and actively reduce technical debt Analysis and insight Build and maintain trustworthy, user-friendly dashboards in Data Studio Perform descriptive, diagnostic, and statistical analyses to surface patterns, operational bottlenecks, and strategic opportunities Partner with data engineers, analysts, and business stakeholders across the group to define consistent metrics and reusable data models Advise colleagues on analytics best practices AI-assisted development and analytics Use Claude and other AI tools extensively — for code generation, review, documentation, debugging, and testing Explore and pilot AI-driven approaches to analysis, such as natural-language querying over the semantic layer, and agentic data workflows Help shape responsible AI adoption in the team: evaluate tools, share what works, and ensure AI-generated code and outputs meet the same quality, security, and governance standards as everything else Exercise sound judgment about AI-generated output — verify rather than trust, and keep data privacy and confidentiality front of mind Ways of working Work as a developer in a Scrum team, using Git/GitHub, code review, and CI/CD workflows Refine user stories and requirements with the Data Product Manager into technical specifications and deliverables …