Product Manager
About the job
About the Product Manager role
The Product Manager leads the strategy, development, and delivery of an enterprise data hub, ensuring it meets the needs of data producers, consumers, and AI-driven use cases. This role defines product vision, translates requirements into actionable user stories, and manages the product backlog to deliver high-impact data and AI capabilities. Working closely with cross-functional teams, the Product Manager drives stakeholder alignment, oversees risk and governance considerations, and uses data insights to guide decisions, measure success, and continuously improve product performance and adoption.
Key Responsibilities:
- Define and communicate a clear product vision and strategy for the organisation’s enterprise data hub, aligned with user needs and organisational goals
- Own the data hub as a product platform, balancing the needs of data producers, data consumers, analytics, and AI-enabled use cases
- Lead user research, customer interviews, and usability testing to identify core problems, unmet needs, and opportunities for data- and AI-enabled improvements
- Analyse quantitative and qualitative data to guide product decisions and measure success
- Translate product strategy into detailed requirements, user stories, and acceptance criteria
- Identify potential risks across the product lifecycle, including data, security, AI, and operational risks; implement mitigation measures and maintain the risk register
- Priorities and maintain the product backlog to ensure delivery of high-impact data and AI capabilities
- Collaborate closely with engineering, design, project management, data owners, and policy teams across directorates
- Communicate product roadmap updates and manage expectations with senior leadership and stakeholders
- Plan and execute product launches; monitor post-launch performance and iterate based on outcomes
- Define what success looks like for the product, including key metrics, data requirements, and reporting/insight mechanisms to track outcomes
- Partner with data owners to ensure data quality, governance, access controls, and appropriate use of data across the product lifecycle
- Identify and validate AI opportunities (e.g. automation, decision support, summarisation, triage) through structured discovery, and translate them into clear use cases, success measures, and incremental deliveries
- Assess AI feasibility and risks, including data readiness, integration constraints, model limitations, ethical considerations, and operational support requirements
- Ensure AI-enabled features are operationally viable, including model lifecycle management, human-in-the-loop controls, monitoring of performance and risks, and integration into day-to-day workflows
- Drive adoption and change enablement for data and AI features (training, communications, stakeholder alignment), ensuring they genuinely extend workforce capacity and improve decision quality
Requirements:
- Minimum 5 years of experience in product management
- Strong analytical and product sense, with experience using data to make decisions
- Proven ability to manage cross-functional teams and drive alignment across multiple directorates
- Experience with go-to-market strategy and end-to-end product lifecycle management
- Strong technical fluency to engage engineering teams on feasibility, constraints, and trade-offs
- Strong communication and stakeholder management skills, including engagement with senior leadership
- Hands-on experience working with data platforms (e.g. data lakes, warehouses, APIs, pipelines) and AI-enabled systems, with sufficient depth to challenge assumptions and make informed product decisions
- Experience delivering or managing data- or AI-enabled products, including understanding feasibility, risks, operational considerations, and change management
