Data Product Manager

<p style="text-align:left"><span>It&#39;s fun to work in a company where people truly BELIEVE in what they&#39;re doing!</span></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p>The Data Product Manager is responsible for owning, shaping, and delivering data products that create measurable business value for the retail organisation. This role serves as the primary bridge between business stakeholders and data, analytics, and data science teams – translating commercial priorities, operational challenges, and strategic questions into well-defined data and analytical solutions. The Data Product Manager ensures that data initiatives are grounded in genuine business need, clearly scoped, and delivered in a way that drives adoption and tangible outcomes, while maintaining fast delivery, high standards of data quality, usability, and governance.<p style="text-align:inherit"></p><p style="text-align:inherit"></p><p><span style="color:#18181b"><b>Minimum Qualifications</b></span></p><ul><li><span style="color:#18181b">Bachelor’s degree in Information Systems, Business, Analytics, Commerce, or a related field (or equivalent practical experience).</span></li><li><span style="color:#18181b">Project Management certification or equivalent (Agile certification preferred).</span></li></ul><p style="color:!important"><span style="color:#18181b"><b>Minimum Experience</b></span></p><ul><li><span style="color:#18181b">5&#43; years’ experience in a data, analytics, business intelligence, or technology environment.</span></li><li><span style="color:#18181b">Proven track record in a role that required translating business needs into data or analytical outputs – e.g. Business Analyst, Data Product Owner, Analytics Lead, or similar.</span></li><li><span style="color:#18181b">Experience working directly with senior business stakeholders and managing competing priorities across multiple domains.</span></li><li><span style="color:#18181b">Demonstrated experience delivering complex, cross-functional initiatives in a large organisation.</span></li><li><span style="color:#18181b">Retail industry experience strongly advantageous.</span></li></ul><p style="color:!important"><span style="color:#18181b"><b>Technical &amp; Tooling Exposure (Advantageous)</b></span></p><ul><li><span style="color:#18181b">Familiarity with data warehousing, BI, and analytics platform concepts.</span></li><li><span style="color:#18181b">Exposure to data science and advanced analytics solution types (e.g. segmentation, forecasting, recommendation).</span></li><li><span style="color:#18181b">Exposure to cloud data platforms and modern analytics stacks.</span></li><li><span style="color:#18181b">Understanding of data governance, privacy, and security principles.</span></li><li><span style="color:#18181b">Familiarity with Agile delivery tools and ways of working.\</span></li></ul><br /><p><span style="color:#18181b"><b>Competencies</b></span></p><ul><li><span style="color:#18181b"><b>Data Product Management:</b> Ability to define product vision, prioritise roadmaps and backlogs, and ensure data products deliver measurable business value.</span></li><li><span style="color:#18181b"><b>Business &amp; Data Acumen:</b> Strong understanding of business processes and the ability to translate complex business challenges into practical data and analytical solutions.</span></li><li><span style="color:#18181b"><b>Stakeholder Engagement &amp; Influence:</b> Builds trusted relationships with business and executive stakeholders, manages competing priorities and influences decisions across multiple domains.</span></li><li><span style="color:#18181b"><b>Requirements Analysis &amp; Translation:</b> Ability to facilitate discovery, clarify ambiguous requirements and translate business needs into clear briefs for data, analytics and technology teams.</span></li><li><span style="color:#18181b"><b>Strategic &amp; Commercial Thinking:</b> Connects data initiatives to strategic objectives, commercial priorities and measurable business outcomes.</span></li><li><span style="color:#18181b"><b>Delivery &amp; Project Management:</b> Strong ability to coordinate complex, cross-functional initiatives, manage scope, timelines, dependencies and risks, and drive delivery to completion.</span></li><li><span style="color:#18181b"><b>Prioritisation &amp; Decision-Making:</b> Makes pragmatic, value-driven decisions when balancing business demand, capacity, dependencies, risk and competing priorities.</span></li><li><span style="color:#18181b"><b>Data Governance &amp; Quality:</b> Understands and promotes data governance, privacy, security, data quality and consistent data definitions.</span></li><li><span style="color:#18181b"><b>Communication &amp; Facilitation:</b> Communicates complex concepts clearly to technical and non-technical audiences and facilitates productive decision-making and discovery sessions.</span></li><li><span style="color:#18181b"><b>Value Realisation &amp; Continuous Improvement:</b> Measures adoption, usage and business impact and uses stakeholder feedback and data to continuously improve data products and outcomes.</span></li><li><span style="color:#18181b"><b>Collaboration &amp; Leadership:</b> Works effectively across data engineering, analytics, data science, architecture and business teams, creating alignment around shared outcomes.</span></li><li><span style="color:#18181b"><b>Data Literacy &amp; Digital Fluency:</b> Understands modern data, BI, analytics and data science concepts sufficiently to shape solutions and engage credibly with technical specialists.</span></li></ul><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p><span style="color:#18181b"><b>Key Responsibilities</b></span></p><p><span style="color:#18181b"><u>1. Business Engagement &amp; Requirements Translation</u></span></p><ul><li><span style="color:#18181b">Act as the primary point of engagement for business stakeholders across retail domains including Commercial, Store Ops, Supply Chain, Finance, Marketing, Smart Shopper, Clothing, Omnichannel and others.</span></li><li><span style="color:#18181b">Proactively engage with business leaders and domain experts to surface data needs, untangle complex problems, and identify opportunities for analytical value.</span></li><li><span style="color:#18181b">Facilitate structured discovery sessions and working sessions to define business questions, success criteria, and the shape of required solutions.</span></li><li><span style="color:#18181b">Translate ambiguous business challenges into clear, well-defined briefs for data engineering, reporting, analytics, and data science teams – spanning dashboards, analytical models, data products, and data science outputs.</span></li><li><span style="color:#18181b">Serve as the voice of the business within the data team, and the voice of data capability back to the business.</span></li></ul><p><span style="color:#18181b"><u>2. Data Product Ownership</u></span></p><ul><li><span style="color:#18181b">Own the vision, roadmap, and prioritised backlog for assigned data products.</span></li><li><span style="color:#18181b">Facilitate prioritisation and capacity planning with Senior Managers and Exec in Data division</span></li><li><span style="color:#18181b">Act as the single point of accountability for the value delivered by each data product.</span></li><li><span style="color:#18181b">Ensure data products are fit for purpose, adopted by end users, and deliver measurable business outcomes.</span></li><li><span style="color:#18181b">Continuously refine priorities based on business value, dependencies, and team capacity.</span></li><li><span style="color:#18181b">Define and monitor success measures, KPIs, and adoption metrics for each product.</span></li></ul><p><span style="color:#18181b"><u>3. Stakeholder Management &amp; Communication</u></span></p><ul><li><span style="color:#18181b">Manage stakeholder relationships across operational and executive levels, balancing competing priorities across multiple domains.</span></li><li><span style="color:#18181b">Maintain clear, proactive communication on progress, risks, timelines, and trade-offs.</span></li><li><span style="color:#18181b">Build trusted relationships that enable honest conversations about what data can and cannot deliver.</span></li><li><span style="color:#18181b">Champion data literacy and the value of evidence-based decision-making across business teams.</span></li></ul><p><span style="color:#18181b"><u>4. Delivery Coordination</u></span></p><ul><li><span style="color:#18181b">Plan and manage delivery across multiple data initiatives, including scope, timelines, risks, and dependencies.</span></li><li><span style="color:#18181b">Coordinate work across data engineers, analysts, data scientists, and external partners where applicable.</span></li><li><span style="color:#18181b">Track delivery progress and ensure milestones and deadlines are met.</span></li><li><span style="color:#18181b">Proactively identify and manage risks, issues, and scope changes.</span></li><li><span style="color:#18181b">Apply pragmatic delivery processes appropriate to the initiative and business area, whether Agile or other project delivery approaches.</span></li></ul><p><span style="color:#18181b"><u>5. Data Governance &amp; Quality</u></span></p><ul><li><span style="color:#18181b">Ensure data products comply with data governance, privacy, and security standards.</span></li><li><span style="color:#18181b">Collaborate with data governance and architecture teams to align solutions with enterprise standards.</span></li><li><span style="color:#18181b">Define and monitor data quality metrics relevant to each product.</span></li><li><span style="color:#18181b">Champion consistent metric definitions, data definitions, and documentation.</span></li></ul><p><span style="color:#18181b"><u>6. Value Realisation &amp; Continuous Improvement</u></span></p><ul><li><span style="color:#18181b">Track adoption, usage, and business impact post-delivery.</span></li><li><span style="color:#18181b">Drive continuous improvement based on user feedback, stakeholder input, and performance data.</span></li><li><span style="color:#18181b">Identify opportunities to enhance or extend existing data products over time.</span></li></ul><br /><p><b>Closing Date: 20 October 2026</b></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left"><i>If you like wild growth and working with happy, enthusiastic over-achievers, you&#39;ll enjoy your career with us!</i></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:left">Discover who we are</p><p style="text-align:inherit"></p><p style="text-align:inherit"></p>