Product Manager

Job Title: Data Product Manager

Location: Hybrid – 1 day per week onsite

Type: 6-Month Contract

Start Date: ASAP

Overview

We are seeking a detail-oriented and innovative Data Product Manager to join our team on a 6-month contract basis. This hybrid role requires one day per week onsite and is ideal for a collaborative, data-driven individual with strong experience translating business and regulatory requirements into technical solutions.

Working closely with the Project Manager and cross-functional teams, you will play a pivotal role in delivering data-centric solutions that enhance governance, manage risk, and ensure regulatory compliance.

Key Responsibilities1. Requirements Analysis & Backlog Management

• Collaborate with the Project Manager to define objectives and business priorities.
• Translate business needs into clear user stories and technical specifications.
• Conduct data mapping, gap analysis, lineage assessments, and transformation rule documentation.
• Maintain and prioritise a delivery backlog aligned to strategic goals and PI commitments.
• Ensure user stories meet INVEST criteria and are continuously refined.
• Identify and resolve potential blockers to ensure smooth delivery.
• Coordinate with QA teams to align on testing and acceptance criteria.

2. Stakeholder Engagement & Collaboration

• Work closely with Business SMEs, developers, and other stakeholders to refine requirements.
• Facilitate workshops and discussions to elicit feedback and refine proposed solutions.
• Communicate clearly about scope, constraints, and trade-offs.
• Use process flows, mock-ups, and data models to support solution understanding.
• Coordinate UAT planning and execution; support end users during rollout.
• Prepare user guides or training materials as needed.

3. Agile Delivery

• Lead backlog presentations during Sprint Planning to support delivery teams.
• Provide clarifications during development, QA, and implementation.
• Ensure solutions meet functional and regulatory requirements, particularly regarding data handling.
• Document final requirements, changes, exceptions, and compliance records.
• Present demos during Sprint Reviews and gather feedback.

4. Data Governance & Continuous Improvement

• Analyse data to evaluate policy effectiveness, identify quality issues, and inform risk management.
• Lead impact assessments and contribute to change prioritisation.
• Recommend enhancements to data handling and remediation practices.
• Maintain audit-ready documentation of decisions and deployment activities.