Analytics Engineer

TL;DR

→ You own the analytics layer — data models, semantic logic, visualization and how insights reach the business.

→ Consultant role across the Nordics, with clients spanning industries form financial services to manufacturing.

→ You work alongside Data Engineers and Cloud Engineers, each owning a distinct layer of the stack.

→ Certifications without a debate. Colleagues who are obsessed with the craft. Freedom to grow your way.

What you'll do

As an Analytics Engineer, you’ll shape how organizations actually use their data. That means understanding how a business operates, designing the models and logic that reflect it, and making sure the output is something people trust and act on.

You come in before the solution is defined. Together with the client, you shape what gets built, then you build it. That includes the visual layer: how dashboards are designed, how reports feel to use, and how data is communicated so it drives action.

You'll work as a consultant in cross-functional delivery teams alongside Data Engineers and Cloud Engineers, each owning a distinct layer of the stack. Your layer is where raw data becomes reliable, structured insight, and where that insight is made visible.

A few examples of what this looks like in practice:

• Migrating a client's legacy reporting environment into Microsoft Fabric, replacing scattered Excel files and static reports with semantic models and curated datasets the business actually trusts.
• Designing a dimensional model for a sales organization where every market had its own definition of "revenue," turning five versions of the truth into one.
• Standing up self-service analytics for a logistics company so operational teams can explore data on their own terms, without routing every question through a single BI person.

The bar for what "done" means here is high: production-grade, observable, secure and used.

What you get

Assignments that accelerate you. Every 6–18 months you're in a new engagement. New industry, new architecture decisions, new stakeholders to earn trust from. You'll face more distinct technical challenges in two years here than most analytics engineers see in five.

Work that's hard to come by elsewhere. Traditional BI is being rewritten, and AI is doing a lot of the rewriting. Here, you shape what comes next: how semantic models, reporting logic and self-service analytics work when AI is embedded in the workflow. This isn't about adding a chatbot to a dashboard. It's about rethinking how insight is structured, delivered and consumed.

Your direction, your call. Go deeper into solution and data model architecture, becoming the person teams turn to when the modelling problem is genuinely hard. Or move toward client advisory and delivery leadership, guiding engagements and shaping how analytics capability is built from the ground up.

People who make you better. Engineers who go deep because they want to, follow the space obsessively, and get restless when things stop moving. That energy is what keeps Redeploy ahead, and it's what you'll feel from day one.

The perks. 30 days vacation · hybrid work and flexible hours · private medical insurance · pension (ITP1) · wellness allowance 5,000 SEK · free choice of tools and tech · free breakfast, soda and snacks · yearly gatherings and AW's · a team with genuine interests outside work — gaming, food, running, padel, golf, football, cycling.

Who you are

You enjoy the technical side of analytics, how data should be structured, how logic should be modelled, how a solution holds together over time. You thrive in dynamic environments and translate complexity into clarity.

You're equally comfortable understanding a client's business challenge as you are modelling the data behind it. You take ownership of the requirements process, guide clients through transformation, and use AI as a natural part of your toolkit, not as something you're planning to explore.

What you bring

• Experience with Azure, Microsoft Fabric or a comparable modern data stack
• Strong SQL skills for modelling and transformation
• Hands-on Power BI experience, (data modelling, DAX and dashboard design with a focus on report UX and clear data communication)
• Understanding of data modelling patterns: dimensional, lakehouse, medallion
• Active use of AI in daily work (AI-assisted development tools like Claude Code, Codex or similar)

Strong plus: dbt or similar transformation frameworks, Git-based analytics workflows, experience in regulated industries, prior consulting experience, Swedish language skills.

About Redeploy

Redeploy is where cloud, data, and AI come together in production. We help Nordic enterprises design, build, and operate modern tech platforms and AI solutions that are secure, scalable, and production-ready. Engineers at heart, we work hands-on across Azure, AWS, and Databricks from strategy to operations.