Analytics Engineer

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
• Maintain technical documentation and release traceability; log bugs and improvement ideas in Jira
• Contribute to continual process improvement
• Governance and security
• Ensure data models and transformations follow established data governance standards, with strict separation of development, test, and production environments
• Apply access control, data classification, and data handling protocols, including proper treatment of personal data (PII) and confidential financial and operational records in line with GDPR