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Senior Enterprise Data Modeler
Tulsa, OK
(Domain, Canonical & Cloud Data Modeling)
Lead the definition and evolution of enterprise data domains, including core entities, relationships, and business semantics, ensuring consistent understanding and reuse across the organization.
Define, maintain, and govern canonical data models that serve as the authoritative semantic foundation for the enterprise API and integration strategy.
Partner with Enterprise Architecture, integration, and API platform teams to ensure canonical models are consistently reflected in API schemas, contracts, and payloads, enabling decoupled and reusable integrations.
Translate business concepts and requirements into conceptual, logical, and physical data models, ensuring traceability from business meaning to technical implementation.
Guide and review Snowflake data models, ensuring they align with enterprise standards and are designed for scalability, performance, and long?term maintainability in a cloud environment.
Establish and enforce enterprise data modeling standards, including naming conventions, key strategies, history patterns, and documentation practices.
Facilitate cross?functional working sessions to resolve semantic differences, drive alignment, and gain organizational buy?in for enterprise and canonical models.
Provide technical leadership, mentorship, and quality oversight for junior data modelers, including design reviews, coaching, and development of modeling best practices.
Manage the lifecycle of enterprise and canonical models, including versioning, impact analysis, and controlled evolution as business needs change.
Communicate complex data modeling concepts clearly to business leaders, architects, engineers, and analysts, ensuring models are understood and correctly applied.
Experience required:
8 years of progressive experience in data modeling, enterprise data architecture, or information architecture roles.
Demonstrated experience defining and delivering enterprise and domain data models in complex, cross?organizational environments.
Hands?on experience producing conceptual, logical, and physical data models that support multiple use cases and lines of business.
Proven experience defining and governing canonical data models, particularly in support of enterprise integration and API strategies.
Experience modeling data for modern cloud data platforms, preferably Snowflake.
Strong understanding of data modeling principles and trade?offs (e.g., normalization vs. dimensional modeling, history management, reuse vs. context?specific design).
Experience working closely with business stakeholders, architects, and engineering teams to translate business meaning into durable data structures.
Demonstrated ability to influence without direct authority, facilitate consensus, and drive decisions across organizational boundaries.
Experience mentoring or leading other data modelers, with responsibility for quality and consistency of modeling outputs.
Senior Enterprise Data Modeler
Tulsa, OK
(Domain, Canonical & Cloud Data Modeling)
Lead the definition and evolution of enterprise data domains, including core entities, relationships, and business semantics, ensuring consistent understanding and reuse across the organization.
Define, maintain, and govern canonical data models that serve as the authoritative semantic foundation for the enterprise API and integration strategy.
Partner with Enterprise Architecture, integration, and API platform teams to ensure canonical models are consistently reflected in API schemas, contracts, and payloads, enabling decoupled and reusable integrations.
Translate business concepts and requirements into conceptual, logical, and physical data models, ensuring traceability from business meaning to technical implementation.
Guide and review Snowflake data models, ensuring they align with enterprise standards and are designed for scalability, performance, and long?term maintainability in a cloud environment.
Establish and enforce enterprise data modeling standards, including naming conventions, key strategies, history patterns, and documentation practices.
Facilitate cross?functional working sessions to resolve semantic differences, drive alignment, and gain organizational buy?in for enterprise and canonical models.
Provide technical leadership, mentorship, and quality oversight for junior data modelers, including design reviews, coaching, and development of modeling best practices.
Manage the lifecycle of enterprise and canonical models, including versioning, impact analysis, and controlled evolution as business needs change.
Communicate complex data modeling concepts clearly to business leaders, architects, engineers, and analysts, ensuring models are understood and correctly applied.
Experience required:
8 years of progressive experience in data modeling, enterprise data architecture, or information architecture roles.
Demonstrated experience defining and delivering enterprise and domain data models in complex, cross?organizational environments.
Hands?on experience producing conceptual, logical, and physical data models that support multiple use cases and lines of business.
Proven experience defining and governing canonical data models, particularly in support of enterprise integration and API strategies.
Experience modeling data for modern cloud data platforms, preferably Snowflake.
Strong understanding of data modeling principles and trade?offs (e.g., normalization vs. dimensional modeling, history management, reuse vs. context?specific design).
Experience working closely with business stakeholders, architects, and engineering teams to translate business meaning into durable data structures.
Demonstrated ability to influence without direct authority, facilitate consensus, and drive decisions across organizational boundaries.
Experience mentoring or leading other data modelers, with responsibility for quality and consistency of modeling outputs.