Lead Data Product Manager

The Walt Disney Company

Lead Data Product Manager responsible for strategic vision and technical fluency in data platforms. Championing data-driven culture across diverse stakeholders in a cloud-native environment.

Posted 7/7/2026full-timeOrlando • California, Florida, Washington • 🇺🇸 United StatesSenior💰 $148,300 - $218,700 per yearWebsite

Tech Stack

Tools & technologies

AWSCloudPythonSQL

About the role

Key responsibilities & impact

Define and own the strategic vision and roadmap for data products across multiple business domains.
Translate high-level business problems into technically grounded data product requirements rooted in consumption-ready data architectures, Kimball-inspired dimensional modeling concepts, and Domain-Driven Design (DDD) bounded contexts.
Align roadmap priorities with overall company objectives and communicate strategic direction to stakeholders at all levels.
Lead requirements discovery and translate business needs into precise, engineer-ready specifications.
Author acceptance criteria that bridge business intent and technical implementation.
Partner directly with Data Product Engineers and Data Architects to bridge business intent and technical execution.
Collaborate with AI/ML and data science teams to define data product requirements that support machine learning initiatives.
Define and enforce data governance standards, metadata management practices, data lineage tracking, and data observability frameworks across the data product portfolio.
Partner with Data Governance and Architecture teams to ensure all data products meet quality, security, and compliance requirements.
Define KPIs and success metrics, monitor product performance, and use feedback to guide continuous iteration.

Requirements

What you’ll need

A minimum of 7+ years in Product Management, data product ownership, or Business Analysis, with a strong focus on data products, business intelligence, or data warehousing — ideally within a cloud-native data stack.
Working knowledge of Snowflake for data warehousing, including an understanding of performance tuning concepts, schema design, and query optimization.
Familiarity with dbt (Data Build Tool) for SQL-based transformation workflows — including model organization, testing, documentation, and version control practices.
Understanding of AWS data services (Lambda, Kinesis, S3, Glue) and their role in event-driven, real-time, and serverless data architectures.
Comfort with Python and/or SQL sufficient to review technical artifacts, evaluate data models, write precise acceptance criteria, and engage substantively with engineering teams.
Exposure to AI/ML workflows, including feature engineering, training data preparation, and model readiness concepts.
Practical understanding of Kimball's dimensional modeling methodologies and Domain-Driven Design (DDD) concepts.
A genuine passion for treating data as a product — defining data contracts, tracking adoption and quality metrics, and delivering measurable business value through trustworthy, well-documented data assets.
Superior verbal and written communication skills, with a proven ability to translate complex technical concepts for executive stakeholders and convert business requirements into precise technical specifications for engineering teams.
Bachelor's or Master's degree in Business, Computer Science, Information Systems, Data Science, or a related quantitative field.

Benefits

Comp & perks

A bonus and/or long-term incentive units may be provided as part of the compensation package
Full range of medical, financial, and/or other benefits

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Data Product OwnershipSQLPythonKimball Dimensional ModelingAcceptance Criteria AuthoringData Lineage TrackingPerformance TuningSchema DesignQuery OptimizationData Observability Frameworks

Soft Skills

Verbal CommunicationWritten CommunicationStakeholder EngagementCollaboration