SUMMARY:
Data Product Owner with strong data engineering skills to lead development of data products
POSITION INFO:
We are seeking a highly skilled Data Product Owner with strong data engineering foundations to lead the development, enhancement, and adoption of data products across key retail business verticals-including Commercial, Supply Chain, Marketing, Loyalty, Finance, and Operations.
The ideal candidate will be responsible for understanding business requirements, analysing data using SQL, and translating those needs into clear developer specifications for data marts, pipelines, and analytics solutions. This role sits at the intersection of business engagement, technical design, and product lifecycle ownership within our modern data platform.
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Key Responsibilities
1. Product Ownership & Strategy
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Own the roadmap, backlog, and lifecycle of data products that support commercial, supply chain, and marketing functions.
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Define product vision aligned to enterprise data strategy and business priorities.
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Work closely with business stakeholders to understand processes, operational goals, KPIs, and reporting requirements.
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Prioritise enhancements and ensure delivery of high-value features and data assets.
2. Business Engagement & Requirements Gathering
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Lead discovery workshops with business teams to capture and refine data requirements.
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Translate business needs into functional and technical specifications for data engineering teams.
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Bridge the understanding between business and technical teams, ensuring clarity, alignment, and value delivery.
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Document current and future-state data flows, source-to-target mappings, and acceptance criteria.
3. Data Engineering Alignment
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Work hands-on with SQL to understand source systems, perform data profiling, validate logic, and support troubleshooting.
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Develop clear developer specifications for data marts, datasets, and pipelines-including schema designs, transformation logic, and data quality rules.
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Collaborate with data engineers and architects to ensure scalable, reliable data solutions.
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Champion best practices in data modelling (e.g., star schema), data governance, and metadata management.
4. Data Mart & Data Product Development
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Lead the design and testing of data marts for commercial, supply chain, marketing, and other business domains.
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Define SLAs, data quality expectations, and monitoring requirements.
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Validate outputs against business expectations and ensure usability for analytics and reporting.
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Drive adoption of data products across the organisation.
5. Delivery, Agile Practices & Stakeholder Management
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Manage backlogs, user stories, acceptance criteria, and sprint planning.
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Communicate progress, risks, and dependencies to senior stakeholders and delivery teams.
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Ensure continuous feedback loops and drive incr
