Director, Data Platforms Engineering

Yum! Brands is seeking a highly technical Director to lead Data Architecture and Engineering within the Data Platforms & Engineering organization.

This role is accountable for defining and executing enterprise data architecture and engineering strategy within the Global Data Hub ecosystem. The leader will establish modern data stack standards, scalable architecture patterns, and engineering best practices to enable governed, high-performing data platforms that support analytics, AI, and operational use cases across the enterprise.

This is a hands-on technical leadership role with direct ownership of the data architecture function and global engineering teams. The ideal candidate brings deep expertise in modern data platforms, strong engineering fundamentals, and the ability to influence both technical and business stakeholders at scale.

Key Responsibilities

Modern Data Stack Ownership

• Own the strategy, roadmap, and continuous evolution of the modern cloud data stack, ensuring alignment with enterprise architecture and scalability needs
• Establish and enforce engineering standards across CI/CD, automated testing, modular pipeline design, and data observability to improve reliability and maintainability
• Drive adoption of software engineering best practices within data teams, elevating code quality, version control, and deployment consistency
• Lead the design and implementation of semantic modeling and metrics layers to standardize business logic and enable consistent data consumption across tools
• Evaluate and introduce emerging technologies, including AI-driven automation, to improve platform scalability, developer productivity, and operational efficiency

Data Architecture Leadership

• Lead the Data Architecture function and team, providing direction on enterprise data modeling, integration patterns, and platform design
• Define and enforce physical and semantic data models to ensure consistency, scalability, and usability across domains
• Develop and promote reusable patterns across ingestion, transformation, and serving layers to accelerate delivery and reduce duplication
• Serve as the senior authority on data architecture decisions, guiding complex design tradeoffs and influencing enterprise standards

Engineering Leadership

• Lead global teams responsible for building and maintaining batch, streaming, and real-time data pipelines supporting enterprise use cases
• Define and enforce engineering standards, including coding practices, review processes, and performance optimization techniques
• Oversee delivery of high-quality data products, curated datasets, and foundational data assets that power analytics and AI initiatives
• Foster a culture of technical excellence, accountability, and continuous improvement across engineering teams

Business Partnership & Data Product Enablement

• Partner with business, product, and technology leaders to translate strategic priorities into data products
• Act as a trusted advisor on platform capabilities, architecture decisions, and data strategy, ensuring alignment with business outcomes
• Balance enterprise standards with domain-specific requirements to deliver flexible yet consistent solutions

People Leadership

• Lead, mentor, and scale global teams across data architecture and engineering, including full-time and partner resources
• Build and sustain a high-performance engineering culture focused on ownership, innovation, and delivery excellence
• Manage vendor and partner relationships to ensure effective and efficient execution of platform initiatives

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 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, data governance, and data quality frameworks

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 skills across both technical and non-technical audiences

Education

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience

Salary Range: $218,600 - $273,100 + eligible bonus + comprehensive benefits