Job Title: Data Product Manager
Location: Hybrid – 1 day per week onsite in Dublin
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 Responsibilities
1. 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.
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