Ralph Lauren Head of Data Product Management

Company Description

Ralph Lauren Corporation (NYSE:

RL) is a global leader in the design, marketing and distribution of premium lifestyle products in five categories: apparel, accessories, home, fragrances, and hospitality. For more than 50 years, Ralph Lauren’s reputation and distinctive image have been consistently developed across an expanding number of products, brands and international markets. The company’s brand names, which include Ralph Lauren, Ralph Lauren Collection, Ralph Lauren Purple Label, Polo Ralph Lauren, Double RL, Lauren Ralph Lauren, Polo Ralph Lauren Children and Chaps, constitute one of the world’s most widely recognized families of consumer brands.

Ralph Lauren unites and inspires the communities within the company and those we serve by amplifying voices and perspectives to create a culture of belonging, ensuring inclusion and fairness for all. We foster a culture of inclusion through talent, education & communication, employee groups and celebration.

The Head of Data Products plays a pivotal leadership role in advancing Ralph Lauren’s enterprise data strategy, a foundational enabler of the company’s next great chapter. The company is actively modernizing core platforms, scaling AI‑driven capabilities, and embedding data‑informed decision‑making across its global consumer ecosystem. The Head of Data Products is responsible for shaping and operationalizing the data product portfolio that fuels Ralph Lauren’s digital operating model, ensuring enterprise data assets are discoverable, trusted, compliant, reusable, and directly aligned to business value and brand elevation priorities.

This leader accelerates the move toward a truly data‑driven, AI‑enabled enterprise, supporting strategic goals such as global DTC growth, personalization at scale, creative and operational agility, and continuous innovation across the value chain. The role ensures that data products deliver measurable value, drive operational excellence, and unlock new digital capabilities while acting as the connective tissue between business stakeholders, data engineering, governance, analytics and AI teams.

The ideal candidate thrives at the intersection of strategy, technology and business value.

• Data Product Strategy & Vision
• Define and champion the enterprise data product strategy, ensuring alignment with business goals, digital transformation priorities, and value roadmaps.
• Develop a multi‑year data product portfolio plan, identifying new opportunities, modernization needs and rationalisation paths.
• Establish enterprise standards for evaluating data product investments, including expected value, feasibility and adoption impact.
• Business Alignment & Value Realisation
• Partner with senior business leaders to translate their priorities into actionable data product roadmaps.
• Define KPIs, success metrics and ROI models for every data product.
• Ensure data products materially improve decision‑making, operational efficiency, omnichannel performance and AI readiness.
• Product Leadership & Operating Model
• Build and lead a high‑performing Data Product Management team.
• Define and institutionalise the enterprise data product lifecycle—from discovery to design, build, launch, iteration and retirement.
• Drive consistent, user‑centric product design emphasising reliability, clarity, trust and accessibility.
• Enterprise Collaboration & Orchestration
• Partner across the Data & Analytics ecosystem:
  Data Engineering, Data Governance, Analytics & AI and Business Units.
• Serve as the alignment hub for priorities, standards, roadmaps and delivery timelines.
• Data Product Delivery & Continuous Improvement
• Oversee delivery of high‑quality, scalable data products.
• Implement ongoing performance monitoring (availability, quality, usage, satisfaction, business outcomes).
• Champion iteration and innovation through user feedback, usage insights and emerging technology.
• Governance, Standards & Risk Management
• Ensure data products comply with enterprise governance, privacy and regulatory standards.
• Proactively manage data and operational risks in collaboration with legal, compliance and security teams.
• Promote…