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Principal Product Manager, Data Products

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: (EDO) Entertainment Data Oracle, Inc.
Full Time position
Listed on 2026-06-20
Job specializations:
  • IT/Tech
    Data Science Manager, Data Analyst, Data Engineering, Business Systems/ Tech Analyst
Salary/Wage Range or Industry Benchmark: 170000 - 200000 USD Yearly USD 170000.00 200000.00 YEAR
Job Description & How to Apply Below

Who We Are

EDO is the TV outcomes company. Our leading measurement platform connects convergent TV airings to the ad-driven consumer behaviors most predictive of future sales. EDO empowers the advertising industry to maximize media impact, optimize creative performance, and know the fair value of every impression — across linear and streaming for an increasingly programmatic world. By combining immediate engagement signals with world-class decision science and vertical AI, EDO equips industry leaders with syndicated, investment-grade data that aligns media to business results — with detailed competitive, category, and historical insights.

Leading brands, agencies, networks, streamers, and studios trust EDO’s TV intelligence to know what works.

EDO is headquartered in New York City and Los Angeles with an office space in San Francisco. We recognize the benefits of hybrid working, and want to create the best balance to ensure we can continue working together effectively. For those who reside full-time in NYC, SF, or LA: we have a hybrid work policy of three days in the office and two remote days.

To learn more about the work we do at EDO, please visit EDO Press.

The Role

As a Principal Product Manager, Data Products at EDO, you will own the strategy, development, and evolution of EDO’s core data products — the foundational datasets, metrics, and data models that power our analytics, measurement, and client-facing applications.

You will sit at the center of Product, Data Science, and Engineering, ensuring that EDO’s data is reliable, scalable, and usable across the organization. You will define how raw data is transformed into structured, governed, and reusable data assets that enable both internal teams and client-facing products.

This role sits at the intersection of Media Analytics, Data Science, and Engineering, with broad influence across teams. You will lead through both direct ownership and cross-functional alignment, setting standards, driving consistency, and ensuring that EDO’s platform delivers consistent, high-quality data that can scale across use cases, clients, and products.

What You Will Do
  • Define and own the roadmap for EDO’s core data products, including datasets, data models, and metric layers.
  • Establish a clear strategy for how data is structured, standardized, and reused across the platform.
  • Partner with Engineering and Data Science to prioritize and deliver scalable data capabilities.
Data Modeling, Metrics & Semantic Layer Leadership
  • Own the definition and evolution of core metrics, dimensions, and semantic layers.
  • Ensure consistency of definitions across analytics, measurement, modeling, and client-facing products.
  • Lead the development of scalable, extensible data models that support a wide range of use cases.
Data Quality, Reliability & Observability
  • Establish and enforce standards for data quality, validation, and monitoring across all data products.
  • Partner with Engineering to define SLAs/SLOs for data reliability and pipeline performance.
  • Drive improvements in data observability, lineage, and debugging capabilities.
  • Ensure trust and auditability of EDO’s data for both internal and external stakeholders.
Platform Enablement & Self-Service
  • Define the strategy for enabling self-service data access across Product, Data Science, Client Analytics, and Operations.
  • Build data products that reduce friction and accelerate time-to-insight.
  • Drive adoption of standardized data assets and reduce reliance on bespoke or duplicated solutions.
  • Enable downstream product teams to build faster on top of well-defined data foundations.
Cross-Functional Leadership
  • Act as the connective tissue across Product, Data Science, Engineering, and Client Analytics.
  • Lead complex, cross-team initiatives that span multiple systems and domains.
  • Influence without authority, aligning teams on shared goals, standards, and tradeoffs.
  • Mentor and elevate other product managers working on data and platform initiatives.
Governance & Standardization
  • Establish and scale governance frameworks for:
  • Metric definitions and naming conventions
  • Data access, permissions, and privacy
  • Data product lifecycle, ownership, and versioning
  • Drive standardization…
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