Data Product Owner

🕒 April 23

🏢🏡 London – Hybrid

⏰ Full Time

🟢 Junior

🟡 Mid-level

✅ Product Manager

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Multiverse

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2016

📚 Education

🏢 Enterprise

☁️ SaaS

Education • Enterprise • SaaS

Multiverse is a company dedicated to providing equitable access to economic opportunity through professional apprenticeships. It focuses on transforming education and the workforce by identifying, closing, and preventing skills gaps using a platform that leverages AI-powered tools. Multiverse operates by offering personalized learning pathways guided by expert coaches to improve productivity and performance. They work with enterprises to unleash employee potential by building data, AI, and software engineering skills, thereby fueling performance and business transformation. With a mission to make the workforce reflect societal diversity, they empower employees to explore new career paths while tracking measurable ROI of their learning strategies.

📋 Description

• As an Analytics Product Owner, you will design, build and manage analytics products that serve teams across the business - shaping how commercial, operations and learner outcomes decisions get made. • Independently scoping and prioritising roadmaps for analytics products, translating complex stakeholder needs into clear feature requirements and delivery plans • Driving end-to-end delivery of substantial product initiatives, making trade-off decisions between scope, quality and timeline while managing dependencies across multiple teams • Establishing product success metrics and feedback loops, using usage data and stakeholder input to iteratively refine features and guide future product direction • Designing end-to-end data product architectures that balance technical constraints with user needs, making tooling decisions that optimise for maintainability and team capabilities • Identifying architectural bottlenecks in existing analytics systems and driving implementation of scalable solutions that become reference patterns for the team • Translating ambiguous stakeholder requirements into concrete data models and visualisation frameworks, establishing design standards that new team members adopt • Demonstrating deep expertise in core analytics tools (Tableau, Metabase, SQL) and actively evaluating emerging AI and build tools to solve team problems with minimal guidance • Acting as the go-to resource for teammates on core tooling, and driving adoption of new technologies by building proof-of-concepts with a clear articulation of business value • Serving as the go-to expert for specific data domains — able to explain complex data structures, lineage and business context to both technical and non-technical stakeholders • Identifying data gaps and quality issues that impact product decisions, proactively proposing solutions and driving remediation across multiple teams • Translating business problems into data requirements by deeply understanding how domain data flows through systems and influences key business processes and metrics • Proactively identifying and engaging the right stakeholders across multiple teams to shape product roadmaps that balance competing business priorities • Translating complex technical constraints and opportunities into clear business value propositions that secure buy-in from senior stakeholders

🎯 Requirements

• Demonstrated ability to work autonomously across the full data product lifecycle - from discovery and scoping through to delivery and iteration • Deep expertise in Tableau and SQL, with a track record of 2+ years of high-quality analytics deliverables • Strong product instincts: comfortable making trade-offs between scope, quality and timeline without needing close direction • Ability to translate complex stakeholder needs into structured product requirements and delivery plans • Experience identifying and driving improvements to analytics architecture or tooling, not just executing against defined briefs • Meticulous attention to detail • Commitment to Multiverse's mission and values • Experience evaluating and adopting emerging tools - inc AI-powered platforms (e.g. Retool, Replit) (Desirable) • Familiarity with semantic layers (e.g. Cube) (Desirable) • Working knowledge of the education or skills sectors (Desirable)

🏖️ Benefits

• 27 days holiday, plus 5 additional days off: 1 life event day, 2 volunteer days, 2 company-wide wellbeing days (M-Powered Weekend) and 8 bank holidays per year • private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership & wellness resources through Wellhub and access to Spill - all in one mental health support • Hybrid work offering - for most roles we collaborate in the office three days per week with the exception of Coaches and Instructors who collaborate in the office once a month • Work-from-anywhere scheme - you'll have the opportunity to work from anywhere, up to 10 days per year • Space to connect: Beyond the desk, we make time for weekly catch-ups, seasonal celebrations, and have a kitchen that’s always stocked!