Sr Product Manager II, Data Product Management

Sr Product Manager II, Data Product Management

Disney Entertainment and ESPN Product & Technology

Technology is at the heart of Disney's past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney's media business globally.

The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company's media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world.

Here are a few reasons why we think you'd love working here:

• Building the future of Disney's media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come.
• Reach, Scale & Impact: More than ever, Disney's technology and products serve as a signature doorway for fans' connections with the company's brands and stories. Disney+. Hulu. ESPN. ABC. ABC News…and many more. These products and brands – and the unmatched stories, storytellers, and events they carry – matter to millions of people globally.
• Innovation: We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems.

The Data Product team is seeking a Senior Product Manager II to drive measurement strategy and analytics instrumentation across ESPN's portfolio of digital products. The team sits at the intersection of the analytics and business teams who depend on trusted data and the engineering teams who build the systems that produce it – and this role is where those worlds meet.

• You'll own instrumentation outcomes across ESPN digital products driving measurement strategy, schema design, and end-to-end delivery across web, mobile, and connected TV. The scope runs the full lifecycle: from defining what gets measured and why, through implementation and validation support, to ensuring downstream teams have the reliable, well-documented data they can build on.
• Own data collection outcomes for ESPN's digital products – accountable for completeness, accuracy, and usability across your instrumentation domain.
• Define what gets measured, why it matters, and how behavioral signals and event schemas serve analytics, reporting, and experimentation needs.
• Convert stakeholder questions into precise instrumentation specs – events, parameters, identifiers, schemas – that engineers can implement without ambiguity across platforms.
• Drive instrumentation from discovery through launch, orchestrating delivery across Product Engineering, Analytics Engineering, QA, and Platform partners.
• Work directly with engineering to ensure instrumentation is implemented correctly and meets platform standards – the bridge between measurement intent and technical reality.
• Configure and operate the analytics platform stack hands-on: implementation, maintenance, and optimization to support reliable, self-service analysis.
• Proactively identify instrumentation gaps and drive resolution through sharper specs, stronger validation, and tight coordination with engineering and QA.
• Use data to audit tagging and tracking health, surface improvement opportunities, and shape future measurement decisions.
• Mentor peer PMs and share instrumentation expertise across the team.
• You bring deep technical fluency in data collection and instrumentation, strong judgment about what measurement actually matters, and the communication skills to align engineers, analysts, and business leaders. You hold yourself to a standard of data quality that makes the difference between insights organizations trust and data they work around.

Basic Qualifications

• 7 years or more in analytics instrumentation, data product management, or analytics engineering – with a track record of owning outcomes, not just executing tasks
• Deep hands-on experience designing event-based data models and instrumentation schemas across web, mobile, and connected TV – including event taxonomies, parameter design, identifier strategies, and implementable data contracts
• Ability to translate ambiguous business questions into precise instrumentation specifications – closing the gap between what stakeholders need to know and what engineers build
• SQL fluency and hands-on experience in cloud data platforms (Snowflake, Databricks, BigQuery, or equivalent) to validate data quality, investigate anomalies, and own your analysis
• Experience configuring and operating enterprise analytics platforms at scale – owning implementation, validation, and maintenance, not just strategy
• Proven ability to orchestrate cross-functional instrumentation delivery across Product Engineering, Analytics, QA, and platform partners
• A bias for action and an ownership mindset: you solve problems end-to-end and are equally comfortable debugging a data issue and presenting measurement strategy to senior leadership
• You use AI-enabled tools as a genuine force multiplier – this is how you work, not a skill you're developing
• Clear, crisp communication: precise technical specs, accessible explanations of instrumentation tradeoffs for non-technical stakeholders, and the ability to influence across engineering, product and analytics

Preferred Qualifications

• Experience with sports, media, or direct-to-consumer digital products at scale
• Hands-on experience implementing solutions from Adobe's Customer Experience (CX) Analytics suite – Adobe Analytics, Customer Journey Analytics, or Adobe Experience Platform – at enterprise scale
• Expert understanding of media industry measurement solutions (Nielsen, Comscore) and how they're implemented and integrated within a major media organization
• Familiarity with event-driven architectures or streaming data infrastructure and their connection to downstream analytics
• Experience enabling self-service analytics at scale through standardized metrics frameworks, reporting taxonomies, or dashboarding solutions
• Working knowledge of data governance, privacy, and consent frameworks (GDPR, CCPA) and their practical implications for instrumentation design

Required Education

Bachelor's degree in computer science, Engineering, Business, Analytics, or related field, or equivalent practical experience.