Sr Product Mgr

The Walt Disney Company•New York, NY

1d•$148,700 - $199,400•Onsite

About The Position

Disney Entertainment and ESPN Product & Technology is a global organization focused on building and advancing the technological backbone for Disney’s media business. The team combines technology with creativity to develop world-class products, enhance storytelling, and drive innovation and scalability. This role is within the Data Product team, seeking a Senior Product Manager I to oversee data collection across Disney’s Direct-to-Consumer (DTC) streaming products. The position acts as a liaison between analytics, product, and engineering teams, focusing on the implementation of systems that capture high-quality behavioral data. The Senior Product Manager will be responsible for instrumentation outcomes in assigned product areas, translating requirements into detailed implementation specifications and managing end-to-end delivery across web, mobile, and connected TV platforms. Collaboration with Product Engineering and platform teams is key to ensure telemetry accuracy, documentation, and reliability for downstream analytics, experimentation, and personalization.

Requirements

5+ years in analytics instrumentation, telemetry, data product management, or a closely related technical discipline.
Hands-on experience designing event-based data models and telemetry schemas (event taxonomies, parameters, identifiers, data contracts) for web, mobile, or connected TV.
Ability to translate product requirements and business questions into precise, actionable telemetry specifications for engineering teams.
SQL fluency and comfort working in cloud data platforms (Snowflake, Databricks, BigQuery, or equivalent) for telemetry validation and analysis.
Experience driving cross-functional instrumentation delivery across Product Engineering and platform partners.
A bias for action and comfort with ambiguity; ability to make progress and close open questions without a fully defined playbook.
Proficiency in using AI-enabled tools as an accelerant for speed, validation, and problem-solving.
Clear written communication skills for technical specifications, explanations to engineers and business stakeholders, and building trust across functions.

Nice To Haves

Experience in streaming, media, or direct-to-consumer subscription products and understanding how behavioral signals map to product and business metrics.
Familiarity with first-party telemetry infrastructure and data flow from collection to analytics, experimentation, and personalization.
Experience supporting experimentation frameworks (A/B testing, feature flagging) through high-quality behavioral telemetry.
Understanding of privacy, consent, and identity considerations in first-party data collection (GDPR, CCPA) and their implications for instrumentation design.
Ability to improve or standardize telemetry schemas, instrumentation patterns, or documentation practices across product teams.
Familiarity with event-driven architectures or streaming data infrastructure and their relationship to telemetry quality.

Responsibilities

Define analytics instrumentation across Disney's DTC streaming products, ensuring data completeness, accuracy, and quality.
Convert product requirements and business questions into precise telemetry specifications (events, parameters, identifiers, schemas) for engineering implementation.
Drive instrumentation delivery from discovery and solution design through implementation, validation, and launch, coordinating with Product Engineering and Platform teams.
Collaborate with engineering to ensure correct telemetry implementation, reliable performance, and alignment with platform standards.
Proactively identify telemetry gaps and risks, driving resolution through refined requirements and close engineering collaboration.
Ensure telemetry reliably supports experimentation frameworks, personalization, and downstream analytics through consistent, documented behavioral signals.
Utilize data to audit telemetry health and downstream usage, informing future instrumentation decisions.
Improve documentation, share learnings, and contribute to evolving instrumentation schemas and patterns within the team.