Design, document, and maintain Axiom's enterprise data model, ensuring coherence and consistency across disparate systems and platforms.
Establish and enforce data governance policies, data quality standards, and associated assurance mechanisms to ensure the reliability and integrity of organizational data assets.
In coordination with the VP, Enterprise Applications, define and maintain the data architecture roadmap, including effort scoping, dependency identification, and alignment with enterprise technology strategy.
Directly manage the Data Engineer; provide technical mentorship, set priorities, and support professional development.
Serve as the primary data architecture liaison to the Product, Operations, and Data Science functions.
In coordination with the VP, Enterprise Applications, evaluate and determine the technology stack for AI solutions and other data initiatives.
Collaborate with the VP, Enterprise Applications and Integrations Lead to reconcile roadmap priorities and ensure integration-produced data meets enterprise data model standards.
Participate collaboratively in the design and implementation of Model Context Protocol integrations, enabling AI tooling to access Axiom's information assets.
Administer and govern the Databricks environment in coordination with the Data Engineer.
Establish and maintain data documentation standards: entity definitions, lineage, ownership, and access policies.

7+ years of progressive experience in data architecture, data engineering, or a related technical discipline.
Demonstrated experience designing and implementing enterprise data models in complex, multi-system environments.
Substantive knowledge of data governance frameworks and data quality methodologies, including practical production implementation.
Strong SQL DDL and DML skills.
Fluency in at least one general-purpose programming language; Python preferred.
Familiarity with enterprise application platforms relevant to Axiom's environment: Databricks, Salesforce, Workday, or comparable systems.
Demonstrated experience leading technical personnel and developing engineering talent.
Exceptional written and oral communication skills, including the ability to convey complex data concepts to non-technical stakeholders.
Experience with Model Context Protocol (MCP) or analogous AI data access patterns, a plus.
Experience operating within matrixed organizational structures requiring negotiation of priorities across teams.

Data Architect

Key skills