Data Product Manager

Overview

In this role you will translate Experian ECS data strategy into a clear portfolio of data products that deliver measurable value. You’ll align customer and commercial priorities with domain teams and data capabilities, driving a transition to domain-owned data products and self-service analytics. You will shape strategy, manage risks, and track adoption to ensure data investments support acquisition, activation, engagement, and monetisation. This is a cross-functional, impact-focused opportunity at scale within a multi-country setup.

Pay / Benefits

• Hybrid working – 40% office based
• Discretionary bonus
• Pension
• Bupa healthcare
• Sharesave Scheme
• 25 days annual leave

Responsibilities

• Shape the data product strategy and roadmap from strategy and priorities
• Prioritise initiatives based on value, feasibility, dependencies and risk
• Define minimum data product standards (purpose, inputs/outputs, KPIs, privacy, ownership, retirement)
• Create clear ownership across domains and prevent duplicated metrics/pipelines
• Support transition to domain-owned and self-service data operating model
• Maintain integrated view of use cases, data products, onboarding, migration and decommissioning
• Sequence delivery around high-value use cases with product, engineering and analytics
• Identify and manage delivery, data quality, privacy, security, capacity, supplier and operational risks
• Define success metrics (adoption, quality, freshness, time to insight) and connect data delivery to business outcomes
• Track value delivery against business case and re-prioritise as market conditions change
• Ensure priority use cases have evidence of consumer adoption and readiness for operation

Key requirements

• Significant experience in product management, especially data products and data platforms
• Practical experience with domain ownership, self-service data, governance, data migrations or data operating model change
• Experience managing a portfolio of interconnected initiatives
• Strong understanding of the data lifecycle (event design, ingestion, modelling, quality, metadata, lineage, analytics)
• Enough technical fluency to challenge assumptions and connect product decisions to architecture, quality, privacy, reliability and cost
• Strong commercial judgement and ability to link data investments to business value
• Proven ability to influence senior stakeholders and delivery teams without formal authority
• Exceptional organisational skills and a repeatable approach to priorities and risks
• Excellent written and verbal communication, with ability to handle difficult news constructively
• Comfort in a complex, changing environment with incomplete information and forward progress

• stakeholder influence
• communication
• organization
• data products
• data platforms
• domain ownership

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