Manager of Governance & Data Modeling

The Manager of Governance and Data Modeling is responsible for establishing and enforcing enterprise standards for database design, data architecture, and data modeling to ensure consistency, scalability, security, and alignment with business needs. This role provides technical leadership and governance across the organization’s data platforms, with deep hands-on expertise in Snowflake and SQL Server, including access controls, Cortex, data duplication strategies, and platform best practices. The position is accountable for defining and directly leading hands-on data modeling activities, including the development and oversight of conceptual, logical, and physical data models that support high-quality, trusted, and well-structured data assets across analytical and operational environments. This role combines governance leadership with active technical execution to ensure data solutions are designed, modeled, and managed in accordance with enterprise standards. The Manager partners closely with data, technology, and business teams to deliver governed, scalable, and effective data solutions that support performance, usability, compliance, and long-term enterprise value. Responsibilities: Establish and maintain enterprise data governance standards for database design, naming conventions, modeling practices, metadata management, and data lifecycle processes across Snowflake, SQL Server, and related data platforms. Lead the creation, review, and enforcement of conceptual, logical, and physical data models to ensure data structures are scalable, secure, reusable, and aligned with business and reporting requirements. Define and implement policies, standards, and procedures for data architecture, data modeling, data duplication, and platform usage to promote consistency and compliance across the organization. Partner with business stakeholders, data teams, and technology leaders to translate operational and analytical requirements into governed data solutions that support trusted reporting, interoperability, and enterprise decision-making. Establishing governance checkpoints, review processes, and monitoring standards to improve the reliability and usability of enterprise data assets. Lead governance reviews for new and existing data initiatives to ensure adherence to enterprise architecture standards, regulatory requirements, privacy expectations, and healthcare data management best practices. Drive continuous improvement of data governance and modeling capabilities.