Multiverse is the upskilling platform for AI and Tech adoption.
We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today’s workforce.
Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech.
Our learners have driven $2bn+ ROI for their employers, using the skills they’ve learned to improve productivity and measurable performance.
In April 2026, we announced $70 million in strategic funding, led by Schroders Capital, with participation from StepStone Group, Lightspeed Venture Partners and General Catalyst.
At an increased valuation of $2.
1bn, the round makes us Europe’s first EdTech double unicorn.
But we aren’t stopping there.
With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling.
We’re building a world where tech skills unlock people’s potential and output.
Join Multiverse and power our mission to equip the workforce to win in the AI era.
What we needWe're looking for an Analytics Engineer to help build and maintain the data models that power analytics and data science across the business.
You'll develop robust, scalable dbt pipelines and help evolve our data platform — ensuring data is accessible, trusted, and well-structured.
Our core platform (Snowflake, dbt, Airflow) is established and isn't changing.
What is changing is the layer on top: we're rethinking our semantic and BI layer for AI/MCP-driven self-service, so analysts, stakeholders, and AI agents can query trusted metrics directly.
You'll help design the models and metric definitions that make that possible.
This is also a role built around AI-assisted development.
We expect you to use AI tools (e.
Claude Code, Cursor, Copilot) as a normal part of writing dbt models, tests, and docs — while still understanding what's happening underneath, so you can catch when the tooling gets it wrong and work effectively without it.
You'll report to the Director of D.