Product Manager, Data Platform

Mattel • El Segundo, CA

22h

About The Position

The Opportunity: We’re looking for a Product Manager with strong experience in data platforms and integrations to support internal systems at Mattel. This role is focused on customer, marketing, and e-commerce data, with ownership of the end-to-end delivery of data pipelines and integrations into our infrastructure and downstream analytics tools.

What Your Impact Will Be: Own the roadmap for marketing and e-commerce data capabilities across ingestion, transformation, warehousing, and delivery to reporting and activation tools. Lead buildout and ongoing improvement of our data foundation for marketing and e-commerce data, including source onboarding, modeling, and dataset readiness for reporting and teams. Drive integration work end-to-end: define requirements, partner with engineering, coordinate with vendors/agencies, manage delivery, and handle rollout and support. Plan and deliver the sunset of legacy data warehouse solutions, including migration strategy and stakeholder cutover planning. Own data QA and reliability: Define data quality checks (completeness, accuracy, freshness, schema changes). Partner with QA/engineering on automated tests and validation processes. Set and manage SLAs for key datasets and pipelines. Put monitoring in place for pipelines and integrations: Define what we monitor (pipeline health, volume anomalies, latency, failures). Set up alerting, triage flows, and clear ownership for fixes. Track issues, manage incident follow-ups, and prevent repeats. Translate business needs into clear data requirements and technical work: Define metrics, data definitions, and dataset contracts needed for marketing and e-commerce reporting. Ensure consistent outputs across sources (web analytics, media platforms, e-comm platforms, CRM/CDP, agencies). Coordinate across teams (Insights, Engineering, QA, Marketing, Agencies, Platforms) to plan releases, manage dependencies, and keep delivery moving. Communicate status and tradeoffs clearly to leadership and stakeholders.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Business, Analytics, or related field (Master’s/MBA a plus).
• 5+ years as a Product Manager (or similar) working on data platforms, integrations, or analytics products (7+ years overall).
• Deep technical understanding of modern data stacks: Data warehousing and integration concepts (modeling, ELT/ETL, DAGs). Databases and analytics/reporting patterns.
• Strong experience owning API-based and file-based integrations (REST APIs, webhooks, batch feeds, SFTP), including vendor/agency data ingestion.
• Proven track record building data QA and monitoring: Data tests, validation workflows, anomaly detection, alerting, incident response.
• Comfortable working with engineering teams through delivery (requirements, scope, prioritization, release planning).
• Clear communicator who can write specs, run cross-team work, and keep stakeholders aligned.

Nice To Haves

• SQL (strong) and/or Python (basic to intermediate).
• Google Cloud experience (preferred).
• Familiarity with tools/patterns for orchestration, observability, and data QA (any equivalents).
• Working knowledge of privacy/security expectations for customer data (baseline handling, access controls, audit needs).

Responsibilities

• Own the roadmap for marketing and e-commerce data capabilities across ingestion, transformation, warehousing, and delivery to reporting and activation tools.
• Lead buildout and ongoing improvement of our data foundation for marketing and e-commerce data, including source onboarding, modeling, and dataset readiness for reporting and teams.
• Drive integration work end-to-end: define requirements, partner with engineering, coordinate with vendors/agencies, manage delivery, and handle rollout and support.
• Plan and deliver the sunset of legacy data warehouse solutions, including migration strategy and stakeholder cutover planning.
• Own data QA and reliability: Define data quality checks (completeness, accuracy, freshness, schema changes). Partner with QA/engineering on automated tests and validation processes. Set and manage SLAs for key datasets and pipelines.
• Put monitoring in place for pipelines and integrations: Define what we monitor (pipeline health, volume anomalies, latency, failures). Set up alerting, triage flows, and clear ownership for fixes. Track issues, manage incident follow-ups, and prevent repeats.
• Translate business needs into clear data requirements and technical work: Define metrics, data definitions, and dataset contracts needed for marketing and e-commerce reporting. Ensure consistent outputs across sources (web analytics, media platforms, e-comm platforms, CRM/CDP, agencies).
• Coordinate across teams (Insights, Engineering, QA, Marketing, Agencies, Platforms) to plan releases, manage dependencies, and keep delivery moving.
• Communicate status and tradeoffs clearly to leadership and stakeholders.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level