Ralph Lauren Head of Data & Analytics Platforms

About the role

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.

Responsibilities

• 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
• 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
• Collaborate with engineering leadership to align platform capabilities with architectural vision and delivery priorities

Requirements

• 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 & Knowledge

• Expertise in data governance, security, and compliance frameworks
• Strong understanding of FinOps and cost optimization strategies
• Excellent stakeholder management and communication skills

Qualifications

• 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

Benefits

• 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.

Pay

Competitive salary and benefits package.

Schedule

Full-time, Monday-Friday.