Content Data Product Manager

The Walt Disney Company; Santa Monica (CA); On-site; USD 118,000 - 158,000; Full time

Job summary

The Walt Disney Company is seeking a Content Data Products Product Manager II to drive end-to-end feature delivery for the content viewership data ecosystem across Disney+, Hulu, and ESPN+. You will partner with data engineers, analysts, and stakeholders to translate data signals into actionable insights and value.

You will refine backlogs, craft user stories, monitor data quality, and collaborate with Engineering, Data Science, and Governance to ensure reliable data products that meet business

Qualifications

• 3+ years of product management experience in data platforms or analytics-heavy roles.
• Bachelor’s degree or equivalent work experience.
• Foundational understanding of Big Data ecosystems and SQL.
• Ability to break down work into MVPs and iterations.
• Strong written and verbal communication skills.

Responsibilities

• Lead end-to-end delivery of feature sets, including backlog refinement and user story creation.
• Support senior PMs on large-scale initiatives and learn from the process.
• Act as primary point of contact for stakeholder inquiries and data quality issues.
• Create and maintain data dictionaries and user guides.
• Collaborate with Engineering, Data Science, and Governance teams to ensure reliability.
• Monitor data product health and coordinate with Data Reliability Engineering to resolve incidents.

Skills

Product management

Agile methodologies

Scrum

Data analysis

Stakeholder management

Communication

Education

Bachelor's degree

Tools

Tableau

Looker

Snowflake

Databricks

Airflow

SQL

Job description

The Walt Disney Company is seeking a Content Data Products Product Manager II to drive end-to-end feature delivery for the content viewership data ecosystem across Disney+, Hulu, and ESPN+. You will partner with data engineers, analysts, and stakeholders to translate data signals into actionable insights and value.

You will refine backlogs, craft user stories, monitor data quality, and collaborate with Engineering, Data Science, and Governance to ensure reliable data products that meet business