Manager, Data Product Engineering

Manager, Data Product Engineering

Location: Orlando, Florida / Glendale, California / Seattle, Washington / Anaheim, California

Business: Disney Experiences

Date posted: Feb. 09, 2026

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 My Disney Experience  app and Hey, Disney!

• 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. 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.
• 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.

• Experience:
  
  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. Proven experience in leading and managing data engineering teams, including experience managing Lead Engineers.
• Leadership & Management
  
  Skills:
  
  Demonstrated ability to inspire, motivate, and develop technical talent. Strong skills in hiring, performance management, conflict resolution, and fostering a collaborative team environment.
• Strategic & Product Mindset:
  Deep understanding of data as a product, ability to define product vision, build roadmaps, and drive execution. Proven ability to secure organizational buy‑in and drive cross‑functional alignment on data strategy.

• Expert‑level understanding and practical experience with Snowflake for data warehousing and performance optimization.
• Extensive experience with dbt 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 principles to complex data architectures.
• Exceptional written and verbal…