Senior Data Product Manager - EPH Digital Products

Description

Are you passionate about turning complex data challenges into clear, scalable product solutions?

Do you enjoy leading through ambiguity, shaping roadmaps, and helping teams deliver high-quality outcomes in an evolving AI-enabled environment?

About our Team

The Enterprise Data & Analytics (EDA) team’s vision is a future where every colleague has trustworthy data they confidently use to streamline processes, drive smarter decisions and accelerate growth. We develop solutions for managing master data, provide capabilities to manage and govern data assets, and provide analytical platforms to deliver valuable business insights.

The Enterprise Product Hub (EPH) is central to that vision. EPH masters Elsevier’s saleable product data – bringing books, journals and a growing range of other products under a single governed model – and currently publishes it to around thirty consuming systems across the business. As Elsevier's product portfolio grows, so does EPH's remit, and the work ahead for the analysts, engineers and product specialists behind it.

About the Role

The Senior Data Product Manager owns a defined area of the EPH product estate – the attributes that enable us to sell a product, from what it's called to how it's identified and how it's sold. You will take your functional direction from the Head of Product Data, and will report indirectly to the Senior Director of EDA.

This role complements the existing product management by taking responsibility for a current gap in our data estate: the ingestion and publication of digital product data. It's an opportunity for a greenfield build – a digital product lifecycle solution to enable publication of digital product data across A&G, Health and Corporate Markets, alongside the existing books and journals data.

This is a delivery-first role: you will work closely with EPH business and engineering colleagues and represent EPH's position in cross-team decisions, with a meaningful second strand; coaching and growing the analysts around you.

Your success will be measured by the quality of the decisions you make under ambiguity, the analysts you grow, and – above all – the extent to which the product data you own helps Elsevier go to market more effectively and makes the customer buying experience better.

Responsibilities

• Engage direct and indirect stakeholders to elicit requirements against our evolving product data model and translate these into clear, actionable specifications from concept through to live release.
• Capture and articulate business value, ensuring work is prioritised based on outcomes and benefit to Elsevier as a whole.
• Make prioritisation and scope decisions across maintenance activities, programme delivery, and longer-term roadmap trade-offs.
• Build strong relationships across business and engineering teams and manage internal consumers through adoption, training, guidance, and documentation.
• As the team shifts towards Spec-Driven Development, write tighter, more testable requirements up front – with a core focus on clarity, constraints and success criteria, which improve AI-assisted delivery.
• Coach and develop junior and mid-level analysts, support onboarding, and contribute to recruitment activities.
• Take ownership of a defined product area, shaping roadmap priorities, success measures, and long-term planning.
• Contribute to data governance practices, system onboarding, and the creation of data and data flow documentation to aid understanding in the wider business.

Requirements

• Experience writing clear, well-constrained requirements and specifications, and genuine interest in adapting your practice to AI-assisted delivery methods.
• A track record of operating independently – owning a product or workstream end-to-end, making prioritisation and scope calls under ambiguity.
• Curiosity and sound judgement, with the ability to work effectively from incomplete information and adapt to changing priorities.
• Proven senior stakeholder management experience across business and engineering teams in complex, multi-stakeholder environments.
• Deep knowledge of data management practices, ideally encompassing master data management (MDM), data governance and metadata management.
• Practical experience with an MDM platform is advantageous.
• Demonstrated experience coaching and developing junior or mid-level analysts.
• Product management, product owner experience, or familiarity with academic publishing or large federated enterprise MDM environments would be beneficial.
• Work in a way that works for you
• We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
• Working Pattern
• Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
• About the Business
• A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world
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• We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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