Data Modeling & Platform Manager

Summary:

The Data Modeling, BI Platform & Governance Manager is responsible for designing, documenting, governing, and supporting the enterprise analytics data layer that powers reporting and self-service dashboards. This role works closely with the Data Engineering team to define data models, validate ETL outputs for accuracy, maintain the data catalog and documentation, and ensure the final “gold” datasets are accurate, reliable, and business-ready.

This role also manages the organization’s Tableau environment for self-service analytics, including permissions, dashboard support, training, and user enablement, while partnering with Legal on privacy compliance, data deletion requests, and other governance-related questions.

Responsibilities:

• Partner with Data Engineering to define source-to-target data requirements, transformation logic, and business rules for analytics datasets.
• Document data models, ETL transformation steps, metric definitions, and the rationale behind modeling decisions to support transparency, consistency, and maintainability.
• Review and QA ETL outputs and final curated datasets to ensure accuracy, completeness, and alignment with business expectations.
• Maintain enterprise “gold” tables used for downstream reporting, analytics, and self-service dashboards
• Own and maintain the data catalog, business glossary, and supporting documentation for key data assets
• Partner with business stakeholders to gather, clarify, and prioritize analytics data requirements for the Data Engineering team.
• Administer the Tableau environment, including workspace organization, user access, permissions, and content governance.
• Support dashboard adoption by training users, enabling self-service development, and providing ongoing Tableau guidance and best practices.
• Help establish and enforce data governance standards, including data definitions, stewardship practices, access controls, and reporting consistency.
• Serve as the operational point of contact for Legal and Privacy-related data requests, including deletion requests, access questions, retention-related issues, and compliance support.
• Identify opportunities to improve data trust, reporting efficiency, documentation quality, and user experience across the analytics ecosystem.

Experience:

• Bachelor’s degree in Business, Analytics, Information Systems, Computer Science, or a related field, or equivalent experience.
• 5+ years of experience in BI, analytics engineering, data modeling, data governance, or related analytical/data operations roles.
• Strong SQL skills and experience working with relational data structures and analytics-ready datasets.
• Experience defining data requirements, validating data accuracy, and supporting ETL or ELT quality checks.
• Demonstrated experience documenting data models, business rules, metric definitions, and transformation logic.
• Experience maintaining or supporting a data catalog, data dictionary, or similar metadata documentation process.
• Hands-on experience administering or supporting Tableau or a similar BI platform.
• Experience managing permissions, access controls, and self-service reporting environments.
• Strong communication skills and ability to work across technical, business, and legal stakeholders.
• Ability to manage multiple priorities in a fast-paced, cross-functional environment.

Preferred Experience:

• Experience in entertainment, hospitality, venues, media, sports, or customer-facing operations.
• Familiarity with data governance programs, privacy compliance, and data lifecycle practices.
• Experience supporting data deletion or privacy request workflows.
• Familiarity with Tableau governance, workbook standards, and dashboard adoption/training.
• Experience working with modern cloud data platforms and analytics tooling.
• Experience translating business requirements into technical data specifications for engineering teams.

The annualized base salary range for this position in California is $105,000 to 145,000. The base salary offered will factor in internal equity and may also vary depending on the candidate's geographic region, job-related knowledge, skills, and relevant experience, among other factors.