Director, Data Platforms Engineering

Key Responsibilities

• Serve as a primary representative of Data Platforms & Engineering within Yum! to executive leadership, building trusted relationships with senior business, technology, and market leaders while influencing enterprise strategy, technology investments, and platform priorities.
• Develop and deliver executive-level communications, business cases, strategic roadmaps, and operational reviews, translating complex technical concepts into clear business outcomes and actionable recommendations for senior leadership and C-level stakeholders.
• Lead a globally distributed organization supporting enterprise data platforms, establishing operating models, execution frameworks, and accountability mechanisms that support Yum!’s AI, Data & Analytics strategy.
• Build high-performing technical teams through coaching, succession planning, and organizational development while driving prioritization across competing business and technology demands.
• Own budget planning and financial stewardship across assigned platforms, tooling, vendor relationships, and delivery functions.

Modern Data Stack Ownership

• Own the strategy, roadmap, and continuous evolution of the modern cloud data stack, including Snowflake, dbt Core, Airflow/Astronomer, Monte Carlo, AWS, and related technologies.
• Evaluate and introduce emerging technologies, including AI-driven automation, to improve platform scalability, operational efficiency, and speed of delivery.

Enterprise Data Platform Strategy

• Define and execute the long-term vision, roadmap, and operating model for enterprise data platforms in partnership with AIDA leadership.
• Drive platform standardization and modernization efforts across brands, functions, and technology teams while influencing investment decisions and technical priorities.
• Lead strategic vendor partnerships, contract negotiations, and commercial discussions while evaluating build-versus-buy decisions.

Data Platform Leadership

• Lead globally distributed teams across Data Architecture, Engineering, and Operations, providing strategic direction, organizational leadership, and technical oversight for enterprise data platforms.
• Establish enterprise architecture patterns, engineering practices, and operational processes that improve platform quality, resiliency, maintainability, and speed of delivery.
• Oversee delivery and support of enterprise data products, platform capabilities, and foundational datasets that power analytics, AI, and operational decision-making.
• Drive continuous improvement through automation, observability, performance optimization, and operational excellence.
• Serve as the senior authority for platform architecture and engineering decisions, guiding complex technical tradeoffs and influencing enterprise technology standards.

Business Partnership & Data Product Enablement

• Partner with business, product, technology, and BYTE Engineering leaders to translate strategic priorities into scalable data products and platform capabilities.
• Act as a trusted advisor on platform capabilities, architecture decisions, and data strategy, ensuring alignment between technical investments and business outcomes.
• Drive adoption and measurable value of enterprise data products while ensuring solutions are scalable, reusable, and aligned with broader enterprise technology roadmaps.

Talent & Organizational Development

• Lead, mentor, and scale global teams by defining talent strategies, organizational structures, and capability development plans that support long-term growth and evolving business needs.
• Build and sustain a heart-led, high-performance culture focused on ownership, innovation, collaboration, and delivery excellence.

Experience Qualifications & Requirements

• 12+ years of experience in data engineering, data platforms, or data architecture.
• 5+ years of experience leading global, distributed technical teams.
• Proven track record of owning and delivering enterprise-scale data platforms and architecture.
• Experience operating effectively in complex, matrixed organizations.
• Technical Skills:
  • Deep expertise in modern data platforms, including Snowflake, dbt Core, Airflow/Astronomer, and AWS.
  • Informatica IICS experience is a plus.
  • Experience with data observability tools such as Monte Carlo or similar platforms.
  • Strong background in data modeling, including physical, semantic, and domain-oriented approaches.
  • Proven experience designing and building scalable batch and real-time data pipelines.
  • Solid understanding of distributed data systems, platform operations, observability, and data quality practices.
• Leadership Skills:
  • Demonstrated ability to influence senior stakeholders and shape technical and business strategy.
  • Strong capability to translate business needs into scalable technical solutions.
  • Proven experience building and leading high-performing technical teams.
  • Excellent communication, presentation, stakeholder management, and executive relationship-building skills.
• Education:
  • Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.