Summary
As a Data Product Manager, you will lead the development and lifecycle management of data-driven solutions, bridging the gap between business goals and technical execution. Your role will encompass requirement gathering, backlog ownership, stakeholder coordination, and ensuring the successful delivery of solutions within an Agile framework.
Core Responsibilities
- Requirements Definition & Backlog Ownership
- Collaborate closely with the Project Manager to capture business objectives, functional needs, and priorities.
- Translate high-level business needs into detailed user stories and technical specifications.
- Conduct in-depth analyses such as data mapping, lineage tracing, gap assessments, and evaluation of system functionality.
- Maintain and continuously refine a prioritised backlog in line with Program Increment (PI) goals, ensuring alignment with strategic priorities.
- Evolve user stories over time to meet INVEST standards and ensure clarity and readiness for development.
- Identify potential blockers early and work with cross-functional teams to resolve issues efficiently.
- Coordinate with Quality Engineering to align on test plans and acceptance criteria.
- Stakeholder Engagement & Collaboration
- Partner with business SMEs, technical teams, and other stakeholders to validate and refine requirements.
- Facilitate structured workshops to collect feedback and requirements while balancing feasibility and business value.
- Communicate project constraints, trade-offs, and interdependencies transparently.
- Present solution options and lead collaborative discussions to refine approaches.
- Use visual aids such as workflows, wireframes, and data models to clarify proposed designs.
- Manage User Acceptance Testing (UAT) by coordinating participants, documenting results, and aligning outcomes with expectations.
- Create and maintain training documentation; support end users and operational teams during implementation.
- Agile Delivery & Execution
- Present prioritised backlog items during Sprint Planning and support the team in defining sprint goals.
- Serve as the lead analyst throughout development, QA, and deployment phases-providing clarifications and resolving issues.
- Verify that the implemented solution behaves as expected, particularly in terms of data management and business logic.
- Maintain comprehensive documentation covering requirements, change requests, exception scenarios, and compliance metrics.
- Deliver product demos during Sprint Reviews and gather actionable feedback from stakeholders.
- Data Governance & Continuous Improvement
- Leverage data analysis to evaluate current processes, identify data quality issues, and understand compliance risks.
- Collaborate with stakeholders to assess the impact, cost, and value of proposed changes to inform prioritisation.
- Recommend and implement improvements in data management processes based on analytical findings.
- Keep detailed records of key decisions, approvals, and deployment activities to support transparency, auditability, and team communication.
Required Qualifications
- Strong background in Data Analysis or Business Systems Analysis within complex, data-intensive environments.
- Experience with regulatory, data privacy, and compliance-focused projects.
- Excellent interpersonal and analytical skills, capable of working across business and technical domains.
- Adept at critically assessing business needs and independently forming and translating solutions into technical requirements.
- Solid understanding of:
- Data governance practices, classification, and retention policies
- System integration and legacy system analysis
- SQL and data querying tools
- Practical experience with Agile or hybrid delivery methodologies and backlog management tools.
- Comfortable discussing technical constraints and collaborating with developers to ensure feasibility.
- Proven ability to manage competing priorities and drive progress amid ambiguity.
- Proficiency with tools such as JIRA, Confluence, Miro, or equivalents.
- Experience in insurance or other regulated industries is a strong advantage.
Key Attributes & Mindset
- Compliance-Oriented: Understands and prioritises regulatory requirements and risk mitigation.
- Team Player: Builds strong relationships with stakeholders to deliver high-impact, value-aligned solutions.
- Detail-Focused: Diligent in capturing and applying field-level logic, rules, and exceptions.
- Clear Communicator: Able to convey technical and analytical insights in business-friendly language.
- Proactive Problem-Solver: Anticipates challenges, takes ownership, and drives resolution.
- Change Facilitator: Uses structured analysis and a strategic lens to guide organisations through data transformation initiatives.
