Director of Data Products

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 skills. 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.

Why this role

Every one of Multiverse's 800+ employees needs data to do their job well, and in the AI era - our ability to leverage data is more important than ever!

As Director of Data Products, you will own the platform, the products, the tools, the processes and the self-serve layer, so that the answer arrives before the request does.

You will be a force-multiplier for the quality, velocity and impact of Multiverse's decision making, and a driving force behind how data and AI are leveraged across the entire business. You will ensure that how we interact with data and deliver data products fully realises the potential of AI.

You will sit in the Data & Insight leadership team, reporting to our VP of Data & Insight, with a seat in company-wide planning and governance forums. You will manage 8 analytics engineers and developers within a wider team of ~20, collaborating with senior stakeholders across the org to coordinate a complex set of competing needs.

What you'll own

Data leverage across Multiverse

• The platform, products and self-serve layer that ~800 people use to find, understand and act on our data — reducing the dependency on Data & Insight to answer questions others could answer themselves.

• Direction on tooling: evaluate the options, make the call, take the organisation through the change.

• Curation of our semantic layer so it covers Multiverse's core business concepts, data and metrics — with clear ownership and stewardship agreed with Domain D&I Leads and business stakeholders, and core architecture aligned with the Director of Data Engineering.

• Governance embedded through the platform itself — quality, definitions, stewardship, access — so that trust and speed stop being a trade-off.

• Real adoption, through documentation, training and support that reaches every relevant domain. Optimising the user experience alongside secure controls and seamless interconnectivity (APIs, MCPs).

Cross-functional roadmap delivery

• D&I's operational planning process: around 50 quarterly projects properly scoped, clearly defined and appropriately resourced, with capacity reallocated as priorities move.

• Representation of D&I in company-wide planning and governance forums, bringing a data lens to decisions being made elsewhere in the business.

• A roadmap that reflects genuine business priority rather than the loudest request, with data needs surfaced early.

• Progress against milestones — risks identified ahead of time, blockers raised, solutions coordinated.

Operational excellence

• Driving the team's cycle planning, standups and retrospectives, run so they are genuinely useful and action-oriented.

• Standards, playbooks and best practice for how work is scoped, how handoffs happen and how outputs are documented — with AI embedded where it creates real leverage.

• Fair triage of inbound support and feature requests, and an escalation route for issues that cross domain boundaries.

• D&I's own operational metrics — project velocity, support throughput, self-serve adoption — tracked and improved. Operational tooling (Asana, Claude) kept current and visible.

People leadership

• Day-to-day leadership of our Analytics Engineers and Analytics Developers: weekly 1:1s, development conversations, meaningful goals.

• Skill gaps identified and closed, through formal training, peer learning or stretch work.

• Fostering a high-performance team culture built on accountability, collaboration and continuous improvement.

• Hiring and onboarding as the team grows.

What we're looking for

Few people will bring every one of these. If you are strong across most, we would like to hear from you.

• 10+ years in data, analytics or technical operations, including 3+ years managing and developing technical teams such as analytics engineers or BI developers.

• Evidenced use of AI to make a measurable difference to how an organisation uses its data, or how a data team operates — and the ability to lead others into those ways of working. This is a high bar for us: we are past curiosity.

• A track record of making data genuinely self-serve in a complex or scaling organisation, with governance — quality, definitions, stewardship, access control — as part of how you did it.

• Ownership of operational planning for a data team: capacity, prioritisation, agile-style ceremonies, delivery against a busy roadmap, and the project tooling (Asana, Jira or similar) that holds it together.

• Credibility with senior stakeholders across functions — able to hold your own in a planning room, translate complex plans for technical and non-technical audiences, and build trust across the business.

• A real interest in developing people, with the judgement to coach, challenge and support individuals at different stages of their careers.

• Organised, detail-minded, and calm in ambiguity — pragmatic enough to make progress before the picture is complete.