Head Of Data And Analytics Platforms

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 Laurens reputation and distinctive image have been consistently developed across an expanding number of products, brands and international markets. The Companys 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 worlds 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.

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The Head of Data & Analytics Platforms plays a pivotal leadership role in advancing Ralph Lauren’s enterprise Data Strategy—one of the core enablers of the company’s Next Great Chapter: Drive agenda. Ralph Lauren has articulated a multi‑year transformation strategy anchored in advanced technology, data, AI, and analytics as critical levers for long‑term growth, operational excellence, and brand value creation. The company is actively modernizing its core data and analytics platforms, scaling enterprise AI capabilities, and embedding data‑driven decision‑making across its global consumer ecosystem.

Ralph Lauren’s transformation spans predictive buying, demand forecasting, omnichannel personalization, digital commerce optimization, and elevated customer and associate experiences powered by enterprise‑scale data and AI. The organization leverages modern data platforms, advanced analytics, and machine learning to improve inventory efficiency, enhance product availability, optimize pricing, and enable real‑time consumer engagement across markets and channels—capabilities that directly reinforce the company’s integrated digital‑physical retail strategy and global omnichannel ambitions.

Within this context, the Head of Data, AI & Analytics Platforms is responsible for defining, building, and operating the enterprise platforms that power analytics, AI, and data products at scale. This leader owns the foundational data, analytics platform ecosystem—ensuring it is secure, resilient, scalable, cost‑efficient, and compliant, while enabling trusted, governed, and high‑performance data consumption across the business. The role is accountable for accelerating Ralph Lauren’s evolution toward a truly data‑driven, AI‑enabled enterprise by providing the underlying technology capabilities required to support global DTC growth, personalization at scale, advanced decision intelligence, and continuous innovation across the value chain.

This role ensures that data, analytics, and AI platforms deliver measurable business value, support operational excellence, and unlock new digital and AI‑powered capabilities across the enterprise. Acting as the connective tissue between Data Engineering, Decision Intelligence, Data Products, Governance, Security, and Technology partners, the Head of Data & Analytics Platforms translates strategic intent into scalable platform execution. The ideal candidate thrives at the intersection of enterprise architecture, cloud and data platforms, AI enablement, and business outcomes—bringing a strong balance of technical depth, operational rigor, and strategic leadership.

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• Define and maintain platform operating model including governance, security, and compliance frameworks
• Own platform lifecycle management—from provisioning and scaling to monitoring and optimization
• Manage vendor relationships and contracts for cloud services, data platforms, and AI infrastructure
• Develop and enforce platform standards for interoperability, observability, and resilience
• Lead platform cost optimization initiatives through FinOps practices and usage analytics
• Enable self-service and automation for data ingestion, transformation, and consumption across business units
• Oversee disaster recovery and business continuity planning for all data and AI platforms
• Drive platform innovation roadmap—evaluating emerging technologies and piloting new capabilities
• Ensure platform readiness for AI workloads including model deployment, feature stores, and LLMOps integration
• Collaborate with engineering leadership to align platform capabilities with architectural vision and delivery priorities
  
  

This leader will design, govern, and optimize enterprise-scale data and AI platforms that deliver secure, scalable, and high-performing capabilities for analytics and AI at global scale. They will define platform strategy, establish operational and compliance standards, and ensure seamless integration across technology and business domains. The role requires a strategic mindset—balancing immediate business needs with a long-term platform vision—and strong stakeholder engagement across Technology, Analytics, and Business leadership.

The position reports to the Head, Global Data & Analytics and partners closely with senior leaders in Technology, Data Governance, Enterprise Architecture, Digital, and Business functions to ensure platforms enable data and AI as a sustainable competitive advantage.

Key Responsibilities

Strategic Leadership

• Define and execute the enterprise data and AI platform strategy and roadmap, ensuring alignment with business objectives and technology modernization guidelines
• Establish and enforce Ralph Lauren Data & Analytics technical architectural standards for scalability, resilience, and interoperability
• Drive platform innovation roadmap, evaluating emerging technologies and piloting new capabilities
  
  

Team & Organizational Leadership

• Build and manage a team of Platform Leads responsible for major Data & Analytics platforms
• Promote adoption and enablement through training programs, user-friendly interfaces, and self-service capabilities
  
  

Governance, Security & Compliance

• Ensure platform security, compliance, and high availability, adhering to regulatory and internal governance standards
• Define and enforce platform standards and policies for data quality, lineage, and observability
  
  

Platform Operations & Optimization

• Oversee cloud infrastructure management, ensuring optimal cost-performance balance through FinOps practices
• Implement monitoring, observability, and disaster recovery plans for resilience and business continuity
• Report platform health, performance metrics, and innovation progress to executive leadership
  
  

Enablement & Accessibility

• Drive data democratization by enabling governed access to trusted data assets through self-service tools and APIs
• Ensure platform readiness for AI workloads, including model deployment, feature stores, and LLMOps integration
  
  

Collaboration & Stakeholder Engagement

• Collaborate with engineering and governance teams for seamless delivery and integration of platform capabilities
• Partner with senior leaders in Technology, Enterprise Architecture, Digital, and Business functions to align platform capabilities with strategic priorities
  
  

Vendor & Technology Management

• Manage vendor relationships and contracts for cloud services, data platforms, and AI infrastructure
  
  

Continuously evaluate emerging technologies to maintain a future-ready platform ecosystem

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• Education:
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related field.
• Experience:
• 12+ years in data platform management, cloud architecture, or enterprise data solutions.
• Proven leadership in building and scaling data and AI platforms in a global organization.
• Strong knowledge of cloud technologies (AWS, Azure, GCP), data Lakehouse architectures, and AI/ML enablement.
• Skills:
• Expertise in data governance, security, and compliance frameworks
• Strong understanding of FinOps and cost optimization strategies
• Excellent stakeholder management and communication skills.
  
  

Leadership & Operating Model

• Strategic thinker with ability to translate vision into actionable plans.
• Collaborative leader who fosters cross-functional partnerships.
• Change agent who drives innovation and continuous improvement.
• Strong business acumen with ability to align technology investments to business outcomes.
  
  

Success Metrics (First 12 Months)

• Platform Readiness: Core lakehouse + streaming + semantic layer operational with ≥99.9% availability; feature store in production for top 3 domains.
• Time-to-Value: Reduce data product cycle time by 50% and ML deployment lead time by 60% through DataOps/MLOps automation.
• Quality & Compliance: ≥95% critical data quality SLA adherence; zero high-severity privacy/security incidents; model risk controls audited.
• Adoption & Impact: 5+ AI use cases in production (e.g., demand forecasting, price optimization, personalization, search/recommendations, supply chain ETA).
• Cost Efficiency: ≥20% reduction in compute/storage cost per workload via autoscaling, caching, tiering, and right-sizing; FinOps dashboards in place.
• Talent & Culture: Hiring plan executed; engineering maturity uplift (code reviews, CI/CD, testing coverage, observability KPIs) across all squads.

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