Manager, Data Product Management-DTC

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The Data Product team is seeking a Manager, Data Product Management to lead measurement and instrumentation across Disney's direct-to-consumer experiences, including Disney+ and Hulu. The data collection layer your team designs powers experimentation, data science, and personalization across the business. It determines what the business knows about engagement and product health, and whether that knowledge can be trusted when decisions get made.

You'll lead a team of Data Product Managers driving DTC instrumentation end-to-end: acquisition and purchase flows, account management, subscriber lifecycle, the browse experience, and everything in between. You'll set a high bar for what exceptional measurement work looks like - both technically and as a practice - and stay close enough to delivery risk to know when that bar isn't being met. If you've led a team building a world-class data collection ecosystem, bring considerable technical depth, and have held yourself accountable for whether data was trusted and not just delivered, we'd like to hear from you.

Responsibilities and Duties of the Role:

• Lead and develop the team, setting the standard for DTC data collection and raising the bar across Product & Technology.
• Own the DTC data collection roadmap across the Disney+ and Hulu product experiences, sequencing by business need and evaluating emerging capabilities.
• Drive execution and stay ahead of delivery risk, balancing speed with long-term telemetry health.
• Write and review instrumentation solution designs (events, parameters, schemas) that feed analytics, experimentation, and ML downstream.
• Own data quality outcomes, closing coverage gaps before downstream teams do, increasingly through AI-assisted monitoring.
• Move the team toward intelligent, contract-based instrumentation that scales coverage automatically and accelerates the engineering lifecycle.
• Partner with Data Engineering, Product Engineering, Product Management, and Business Operations on shared measurement goals.
• Represent the team's strategy to senior leaders across the company.

Required Education, Experience/Skills/Training:

Basic Qualifications

• 8+ years in data product management, data instrumentation, digital analytics implementation, or a closely related field.
• Direct experience leading and developing teams in instrumentation, analytics, or measurement, accountable for performance and the team's standards.
• Fluency with AI tools in your own work, and a track record of raising AI fluency across your team.
• Strong product sense applied to measurement: you've owned strategy and roadmap with clear accountability for outcomes.
• Deep understanding of first-party and third-party measurement across web, mobile, and connected devices, and how instrumentation choices affect downstream quality and trust.
• Hands-on technical depth in instrumentation and analytics implementation on enterprise measurement platforms (AEP/CJA, Amplitude, or comparable), with recent hands-on application, not solely oversight.
• Track record of cross-functional execution across Product Engineering, Product Management, Analytics, QA, and Program teams in matrixed organizations.
• Proficiency in SQL and/or Python for data validation, troubleshooting, and analysis.
• Clear communicator who can translate technical tradeoffs into business terms for any audience, including executives.

Preferred Qualifications

• Experience supporting DTC subscription or commerce products at scale: purchase, upgrade, cancellation, or account management analytics.
• Experience building instrumentation for A/B testing and product experimentation at scale.
• Data observability experience: monitoring pipelines for quality, freshness, and schema drift.
• Strong understanding of data governance, privacy, and compliance (GDPR, CCPA) in analytics instrumentation.
• Familiarity with the modern cloud data stack and how analytics data flows downstream.
• Advanced degree in Computer Science, Information Systems, Data Science, or a related field, or equivalent practical experience.

Required Education

Bachelor's degree in Computer Science, Engineering, Business, Analytics, or a related field, or equivalent practical experience.

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