Sr Product Manager II, Data Product Management

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.

• 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 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.

• 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, Big Query, 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.

• 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,…