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Manager, Data Product Engineering

Job in Orlando, Orange County, Florida, 32885, USA
Listing for: The Walt Disney Company
Full Time position
Listed on 2026-02-14
Job specializations:
  • IT/Tech
    Data Science Manager, Data Engineer
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

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!

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.

Key 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. Translate 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.
Qualifications
  • 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 leading and managing data engineering teams, including managing Lead Engineers.
  • Leadership & Management

    Skills:

    Demonstrated ability to inspire, motivate, and develop…
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