Sr. Data Modeler

Responsibilities

• Create a pragmatic model that supports domain autonomy while enabling cross-domain analysis and data sharing.
• Maintain an enterprise ontology, business glossary, and semantic definitions so that important terms and metrics mean the same thing across products and teams.
• Design for reuse, extensibility, regional variation, and future use cases while avoiding unnecessary centralization.

Preferred

• Experience with Databricks, Delta Lake, Unity Catalog, Snowflake, or comparable cloud data platforms.
• Experience with a data catalog, modeling tool, and metadata-management platform.
• Experience supporting global products and multi-region data, regulatory, or data-residency requirements.
• Experience designing semantic models and governed metrics for BI, natural-language data experiences, or AI applications.
• Experience in a regulated, high-scale, or operationally sensitive environment.

Silver

Standardize and validate data; apply common identifiers, canonical entities, conformed dimensions, data-quality rules, and cross-domain integration patterns.

Gold

Deliver governed, business-ready data products, semantic models, certified metrics, and analytics-ready structures for dashboards, self-service analysis, and AI. Ensure traceability from Gold metrics and business concepts back through Silver transformations to authoritative Bronze sources. Define clear rules for when a concept belongs in a domain model, the shared enterprise model, a semantic layer, or a product-specific analytical model. Review and guide physical implementations for performance, maintainability, cost, privacy, and scale. Enable data products and delivery teams Partner with Product Managers and domain leaders to turn business outcomes and use cases into clear data-modeling requirements. Partner with Data Engineers to define schemas, transformations, mappings, data contracts, and implementation patterns. Partner with BI developers to create governed semantic models, reusable measures, and self-service-ready datasets. Facilitate architecture and design reviews; identify duplication, inconsistent definitions, broken lineage, and integration risk early. Provide model patterns, templates, and coaching that enable teams to deliver independently while following enterprise standards. Govern for trust, security, and global scale Embed data quality, lineage, ownership, retention, security classification, privacy-by-design, and access-control requirements into data-model designs. Model regional, regulatory, language, currency, and local-business variations without fragmenting global reporting or shared concepts. Define stewardship and decision rights for enterprise entities, metrics, and reference data. Maintain model documentation and metadata in the organization’s data catalog and modeling tools. Measure adoption, reuse, quality, coverage, and exceptions to drive continual improvement of the North Star model. What success looks like Teams use the same definitions for shared business concepts and key metrics.

New data products can be delivered faster because common models, dimensions, identifiers, and patterns are reusable. Cross-domain reporting is reliable, explainable, and traceable to authoritative sources. Data consumers can discover what data exists, what it means, who owns it, and whether it is fit for use. Regional expansion is supported through intentional extensions rather than isolated local models. Gold-layer analytics and AI experiences use certified semantic definitions rather than reconstructing logic independently.

Required qualifications 7+ years of experience in data modeling, data architecture, data engineering, analytics engineering, or related disciplines. Demonstrated experience designing conceptual, logical, and physical models for complex, multi-domain data platforms. Experience defining or evolving an enterprise data model, canonical model, semantic layer, ontology, or common data model. Strong understanding of dimensional modeling, normalized modeling, data vault or equivalent integration patterns, and lakehouse/warehouse design. Experience designing models for raw, standardized, and consumption-ready data layers in a modern cloud data platform. Proven ability to translate business concepts into unambiguous data definitions, models, mappings, and implementation guidance. Practical expertise in metadata, lineage, data quality, data governance, master/reference data, and data privacy. Strong facilitation and communication skills; able to influence senior stakeholders and delivery teams without relying on direct authority.

Preferred qualifications

As part of our selection process, external candidates may be required to attend an in-person interview with a VERSANT Media employee at one of our locations prior to a hiring decision. VERSANT Media's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law. If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation. You can submit your request to [email protected] . VERSANT Media is committed to fair and equitable compensation practices. We include a good faith pay range for each position to comply with applicable state and local pay transparency laws and to promote equity across our organization. Actual compensation will be based on factors such as the candidate's skills, qualifications, experience, and location and may include additional forms of compensation and benefits such as health insurance, retirement plans, paid time off, etc. VERSANT Media is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at VERSANT via-email, the Internet, or in any form and/or method without a valid written Statement of Work in place for this position from VERSANT's Talent Acquisition team will be deemed the sole property of VERSANT. No fee will be paid in the event the candidate is hired by VERSANT as a result of the referral or through other means.

VERSANT is a leading force in news, sports and entertainment - home to iconic and trusted brands that inspire, inform, and delight audiences. Our unique combination of content, technology and services enriches the cultural fabric, igniting passions, sparking conversations, and connecting people to what they love most. As an independent, publicly traded company, VERSANT brings together powerhouse cable networks - including USA Network, CNBC, MS NOW (formerly MSNBC), Oxygen, E!, SYFY, and Golf Channel - with dynamic digital and direct-to-consumer brands such as Fandango, Rotten Tomatoes, GolfNow, GolfPass, and SportsEngine. Together, these businesses reflect our commitment to delivering exceptional experiences across every screen and service. VERSANT is an industry-changing media company fueled by innovation and an entrepreneurial spirit. With a strong foundation and a forward-looking vision, VERSANT empowers creativity, embraces change, and drives connection in an ever-evolving world.