Senior Data Product Owner

Reporting to the Senior Manager – Data Products, the Senior Data Product Owner is part of the Data team and is responsible for shaping the vision, roadmap, and execution of data products that empower teams with actionable insights and scalable solutions. Working with a cross-functional squad of engineers and data scientists, this role translates complex models and technical workflows into commercial outcomes. You will lead prioritization and Data Products development to increase customer satisfaction and impact. 

This role offers challenges across a wide variety of products and responsibilities, including the opportunity to influence the future direction of the department and products built by the business. It is ideal for a Product Owner who thrives in ambiguity, brings strong technical acumen, and is passionate about driving business value through structured Product Ownership and stakeholder alignment. 

Major Responsibilities 

Product Ownership & Strategy 

• Own and drive the end-to-end delivery of initiatives through governed data products that directly support strategic business priorities and align with enterprise data architecture. 
• Define and communicate the data product vision and strategy. 
• Own the full product lifecycle — from ideation to retirement. 
• Translate business needs into clear, actionable requirements (epics and user stories), maintaining traceability to measurable business value. 
• Lead and contribute to data modeling efforts, ensuring data products are underpinned by sound data modeling theory, including the appropriate level of normalization, dimensional modeling and domain driven design.   
• Partner with domain analysts and data engineers to ensure data products are developed properly and meet defined requirements. 
• Evaluate existing data products to determine opportunities for reuse or extension before defining new ones. 
• Ownership of product versioning, backlog and prioritisation based on value and impact. 
• Monitor product performance and identify optimization opportunities. 
• Continuously discover user needs and track market trends. 
• Serve as the single point of accountability for the data products  

Stakeholder Engagement 

• Act as the key liaison between business units and data teams to ensure data product delivery aligns with business objectives and strategic priorities. 
• Collaborate with stakeholders to prioritize phased delivery, balancing immediate needs with long-term scalability and reuse. 
• Communicate delivery status, risks, blockers, and trade-offs clearly to both technical and non-technical stakeholders. 
• Manage stakeholder expectations and engagement by ensuring their expectations are aligned around timelines, scope, and team capacity, ensuring transparency and shared understanding throughout the delivery lifecycle.  

Agile Delivery 

• Champion a minimum viable product (MVP) mindset to support incremental delivery and early value realization. 
• Provide hands-on coaching to data engineers and other team members to maintain delivery momentum, manage technical debt, and adhere to agile best practices. 
• Champion agile practices within the team, including backlog grooming, sprint planning and daily stand-ups. 
• Support maturing Product Ownership discipline within the Data function through templates, tracking dashboards, playbooks, and shared tooling. 

Qualifications, Skills and Experience 

Must Have: 

• Bachelor’s or Master’s degree in Computer Science, Data Science, Business, or a related field. 
• 5+ years of experience in product management, ideally with a focus on data engineering, analytics, or data platforms.  
• Demonstrated experience in target-state data modelling and collaboration with data architects on scalable models.  
• Strong understanding of product lifecycle management, data governance principles, and Agile delivery.  
• Excellent communication and stakeholder management skills across business and technical teams.  
• Experience with tools such as Jira, Confluence and similar. 
• Basic understanding of logical data modelling SQL, Python and data pipelines. 
• Experience working in Agile / Scrum environments. 

Nice to have: 

• Hands-on experience working with cloud-based data environments such as Databricks, Azure, or equivalent.  
• Understanding od data architecture and analytics 
• Experience in maritime or environmental sectors.