Manager, Data Product Engineering

The Walt Disney Company • Glendale, CA

17h

About The Position

At Disney Experiences Technology, our team creates world-class immersive digital experiences for the Company’s premier vacation brands including Disney’s Parks & Resorts worldwide, Disney Cruise Line, Aulani, A Disney Resort & Spa, and Disney Vacation Club. The Disney Experiences Technology team is responsible for the end-to-end digital and physical Guest experience for all technology & digital-led initiatives across the Attractions & Entertainment, Food & Beverage, Resorts & Transportation, and Merchandise lines of business as well as other initiatives including the MyDisneyExperience app and Hey, Disney! As the Manager of Data Product Engineering, you will be at the helm of our efforts to define, build, and deliver high-value data products across the organization. You will be responsible for leading, mentoring, and growing a team of Data Product Engineers (including Lead Engineers), ensuring they have the support, direction, and resources to excel. This role demands a blend of strong technical acumen, strategic leadership, and exceptional people management skills. Crucially, you will actively champion the alignment of our data product strategy with overarching business goals, ensuring deep collaboration across business units to jointly define and prioritize domain-driven data products. You will foster a culture of innovation and excellence, acting as a key liaison between engineering, product, data science, and business stakeholders to ensure our data assets are robust, accessible, and directly support our company's strategic goals, especially within AI/ML initiatives.

Requirements

• 8+ years of hands-on experience in data engineering, data warehousing, or a related field, with a strong emphasis on building robust, scalable data solutions. including proven experience in leading and managing data engineering teams, including experience managing Lead Engineers.
• Demonstrated ability to inspire, motivate, and develop technical talent. Strong skills in hiring, performance management, conflict resolution, and fostering a collaborative team environment.
• A deep understanding of data as a product, with the ability to define product vision, build roadmaps, and drive execution. Proven ability to not only define data product vision and roadmaps but also to secure organizational buy-in and drive cross-functional alignment on data strategy and the foundational role of domain-driven data products. Exceptional ability to bridge the gap between technical possibilities and business realities, translating complex data concepts into tangible business value.
• Expert-level understanding and practical experience with Snowflake for data warehousing and performance optimization.
• Extensive experience with dbt (Data Build Tool) for advanced data modeling, transformation, and governance.
• Demonstrated expertise in designing and implementing real-time data pipelines using AWS Lambda and AWS Kinesis.
• Strong command of Python for data engineering and automation; familiarity with other languages like Java is a plus.
• Solid understanding of how to prepare and provision data for AI/ML applications and platforms.
• Proficiency in applying Kimball's dimensional modeling and Domain-Driven Design (DDD) principles to complex data architectures.
• Exceptional written and verbal communication skills, with a proven ability to facilitate strategic discussions, gain consensus, and articulate complex technical and strategic concepts to diverse audiences (engineers, executives, business users). Demonstrated ability to influence data strategy decisions and drive adoption of data product best practices across the organization.
• A highly analytical and structured approach to problem-solving, with a track record of tackling complex technical and organizational challenges.
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field.

Responsibilities

• Lead & Develop High-Performing Teams: Recruit, onboard, mentor, and manage a team of Data Product Engineers, including Lead Engineers. Foster a culture of technical excellence, continuous learning, accountability, and psychological safety. Conduct performance reviews, set clear objectives, and support career growth.
• Strategic Data Product Leadership & Business Alignment: Lead the development and communication of our data product strategy and roadmap, actively collaborating with business leaders and stakeholders across all relevant departments (e.g., Marketing, Finance, Operations, Product Management). Drive consensus and alignment on key data domains and ensure our Domain-Driven Design (DDD) approach directly reflects and supports core business processes and strategic objectives. You will be instrumental in translating business strategy into a cohesive data strategy, fostering a shared understanding of data value, and accelerating data-driven decision-making across the enterprise.
• Architectural Guidance & Technical Governance: Provide architectural oversight and technical guidance to your team, ensuring data product designs are scalable, resilient, secure, and maintainable. Champion best practices for data modeling (Kimball, DDD), data quality, governance, and CI/CD for our Snowflake, dbt, AWS Lambda, and Kinesis-based data platform.
• Drive Operational Excellence: Establish and enforce robust processes for data product lifecycle management, including incident response, performance monitoring, cost optimization, and adherence to data governance policies. Ensure reliable and timely delivery of data to support business operations and AI/ML workloads.
• Vendor & Resource Management: Manage budget allocation for your team, evaluate and manage relationships with external vendors and technology partners, ensuring optimal utilization of resources and technologies.
• Innovate & Champion AI/ML Data Readiness: Guide the team in designing and building data products that specifically empower our AI/ML efforts, ensuring data is clean, well-structured, and readily available for feature engineering, model training, and inference. Stay abreast of industry trends in data engineering and AI/ML.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager