About the position
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.
Key Responsibilities
1. Product Ownership & Strategy
Own the roadmap, backlog, and lifecycle of data products that support commercial, supply chain, and marketing functions.
Define product vision aligned to enterprise data strategy and business priorities.
Work closely with business stakeholders to understand processes, operational goals, KPIs, and reporting requirements.
Prioritise enhancements and ensure delivery of high-value features and data assets.
2. Business Engagement & Requirements Gathering
Lead discovery workshops with business teams to capture and refine data requirements.
Translate business needs into functional and technical specifications for data engineering teams.
Bridge the understanding between business and technical teams, ensuring clarity, alignment, and value delivery.
Document current and future-state data flows, source-to-target mappings, and acceptance criteria.
3. Data Engineering Alignment
Work hands-on with SQL to understand source systems, perform data profiling, validate logic, and support troubleshooting.
Develop clear developer specifications for data marts, datasets, and pipelines—including schema designs, transformation logic, and data quality rules.
Collaborate with data engineers and architects to ensure scalable, reliable data solutions.
Champion best practices in data modelling (e.g., star schema), data governance, and metadata management.
4. Data Mart & Data Product Development
Lead the design and testing of data marts for commercial, supply chain, marketing, and other business domains.
Define SLAs, data quality expectations, and monitoring requirements.
Validate outputs against business expectations and ensure usability for analytics and reporting.
Drive adoption of data products across the organisation.
5. Delivery, Agile Practices & Stakeholder Management
Manage backlogs, user stories, acceptance criteria, and sprint planning.
Communicate progress, risks, and dependencies to senior stakeholders and delivery teams.
Ensure continuous feedback loops and drive incremental improvements to data products.
Support project governance, documentation, and release planning.
Technical Skills & Competencies
Technical Skills
Strong SQL skills for data exploration, profiling, validation, and troubleshooting.
Understanding of data engineering concepts: ETL/ELT pipelines, orchestration, data ingestion, and data quality frameworks.
Experience designing or working with data marts, semantic layers, and BI-ready datasets.
Familiarity with modern cloud data platforms (e.g., Azure, AWS, GCP, Snowflake, Databricks)
Practical knowledge of data modelling (dimensional modelling, star/snowflake schemas).
Ability to interpret and design source-to-target mappings and transformation logic.
Product & Delivery Skills
Strong product ownership mindset with experience managing data product roadmaps.
Ability to facilitate requirement gathering and translate insights into user stories.
Skilled in Agile/Scrum methodologies (certification beneficial).
Excellent written and verbal communication skills, especially in translating between technical and non-technical stakeholders.
Business Domain Knowledge
Experience in one or more retail verticals is highly advantageous:
Commercial / Buying & Merchandising
Supply Chain & Logistics
Marketing & Loyalty
Finance / Operations / Store Performance
Qualifications & Experience
Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field (or equivalent experience).
5+ years combined experience across data product ownership, data analysis, or data engineering.
Demonstrated experience building or contributing to data products, data marts, or analytical platforms.
Retail experience is highly preferred but not required.
Experience engaging business stakeholders at all levels.
Key Attributes
Strong analytical and problem-solving mindset.
Curious, detail-oriented, and comfortable challenging assumptions.
Highly collaborative with strong interpersonal skills.
Ability to work in complex, fast-paced retail environments.
Passion for enabling business value through data.
Desired Skills:
- Data Product Owner
- Data Engineering
- SQL
