Ralph Lauren Head of Data & Analytics Platforms

Position Overview

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.

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• Manage vendor relationships and contracts for cloud services, data platforms, and AI infrastructure.
• Continuously evaluate emerging technologies to maintain a future-ready platform ecosystem.

Experience, Skills & Knowledge

• Education: Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related field.
• 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.
• Expertise in data governance, security, and compliance frameworks.
• Strong understanding of FinOps and cost optimization strategies.
• Excellent stakeholder management and communication skills.
• Ability to translate vision into actionable plans and collaborate across functions.
• 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.