Data Product Manager

About the job:

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, Chaps, among others, constitute one of the world's most widely recognized families of consumer brands.

At Ralph Lauren, we unite and inspire the communities within our company as well as those in which 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 Data Product Manager owns the strategy, roadmap, and delivery outcomes for a portfolio of Ralph Lauren's enterprise data products - the shared datasets, analytical assets, and AI-ready data foundations that power decision-making across the business.

Working closely with Data Engineering, Platform, Analytics, and Governance teams, as well as business stakeholders, this role defines what data products should exist, why they matter, and how success is measured - translating business needs into clear product requirements and prioritized roadmaps.

As Ralph Lauren advances its multi-year digital and AI-driven transformation, the Data Product Manager plays a central role in ensuring data products are well-defined, adopted, and continuously improved, while balancing platform constraints, governance requirements, and business value.

At a manager level, this role brings experience owning product strategy and roadmaps, leading cross-functional delivery teams, and managing senior stakeholder relationships in a complex, global organization.

Product Strategy & Roadmap:

- Define the vision, roadmap, and prioritization for assigned data products in alignment with enterprise data strategy and business priorities.

- Translate business needs from stakeholders into clear product requirements and success criteria.

- Balance demand across business units, weighing value, effort, and platform constraints.

- Own the product backlog and ensure it reflects current priorities and dependencies.

Stakeholder & Business Partnership:

- Build strong relationships with business stakeholders to understand decision-making needs and data gaps.

- Act as the primary point of contact for assigned data products, managing expectations and trade-offs.

- Present roadmaps, progress, and outcomes to business and technology leadership.

- Champion data product thinking and adoption across the organization.

Delivery Leadership:

- Partner with Data Engineering Managers and Scrum Masters to translate roadmaps into executable sprint plans.

- Make day-to-day prioritization calls within sprints, while delegating execution details to delivery teams.

- Track delivery progress, risks, and dependencies, and remove blockers where needed.

- Ensure data products are delivered with appropriate documentation, testing, and operational readiness.

Value Measurement & Continuous Improvement:

- Define and track adoption, usage, quality, and value realization metrics for owned data products.

- Use metrics and stakeholder feedback to identify opportunities for iteration or retirement.

- Conduct post-launch reviews to validate whether data products are meeting intended business outcomes.

- Continuously refine the product roadmap based on usage trends and changing business needs.

Governance & Data Trust:

- Partner with governance and security teams to ensure data products meet quality, privacy, and compliance standards.

- Ensure metadata, lineage, and documentation are maintained to support discoverability and trust.

- Surface and help resolve data quality or definitional issues that affect product reliability.

People & Cross-Functional Leadership:

- Provide product direction and mentorship to Product Analysts supporting the portfolio.

- Foster collaboration across Data Engineering, Platform, Analytics, and Governance teams.

- Promote consistent product management practices across the Data Product Management function.

Qualifications:

Required:

- 7 - 10 years of experience in product management, data product management, or related roles, including people or portfolio leadership.

- Proven experience owning the strategy and roadmap for data, analytics, or platform products.

- Strong understanding of data engineering, analytics, and BI concepts, with the ability to converse fluently with technical teams.

- Demonstrated ability to manage senior stakeholder relationships and influence prioritization decisions.

- Experience operating in Agile or product-based delivery models.

Preferred:

- Experience in retail, consumer goods, or digital commerce environments.

- Background delivering enterprise data products, shared data assets, or analytical platforms at scale.

- Comfort working in global, matrixed organizations.

- Exposure to cloud-based data platforms and AI-driven use cases.

Success Measures:

- Clear, well-prioritized roadmaps for owned data products aligned to business value.

- Strong adoption, usage, and satisfaction metrics for data products in the portfolio.

- Predictable delivery against committed roadmaps with minimal rework.

- High stakeholder confidence in product direction and decision-making.

Skills

IT Product Management, IT Product Strategy, Product Roadmap