Director, Data Ontology

DeepIntent•New York, NY

18h•Remote

About The Position

DeepIntent is building the intelligence layer of healthcare advertising. This layer runs on well-structured, well-defined, and human- and machine-readable knowledge. As the company accelerates the deployment of internal and external agentic applications, the quality of our underlying data ontology determines how far and how accurate our applications can be. Ontology is a new and critical function at DeepIntent, and its core purpose is to organize and curate business context and data across the company. You will build it. Your job is to define, document, and govern how DeepIntent understands its own data. You will be creating and implementing the semantic foundation that enables our people and AI agents to reason with veracity across our business and platform.

Requirements

7+ years in data roles with significant focus on data modeling, knowledge management, or semantic architecture
Experience building or contributing to a knowledge graph, data catalog, or enterprise ontology
Strong SQL and data modeling skills; comfort in a cloud data warehouse environment
Ability to drive cross-functional alignment on abstract, contested topics — equal parts technical and organizational
Experience designing data schemas or metadata layers specifically for LLM or AI agent consumption
Background in health informatics, clinical data, or life sciences — not just healthcare advertising
Familiarity with MCP (Model Context Protocol) or API schema design for AI tool use
Familiarity with healthcare and/or media data specifications and standards: ICD-10 codes, claims data, OpenRTB, etc. and how these data can be leveraged

Responsibilities

Design and maintain DeepIntent's healthcare advertising ontology across healthcare and media domains
Map external standards (i.e. ICD-10, etc) to DeepIntent's internal data model, when applicable
Build and manage a knowledge graph that connects our data and products into a coherent, traversable semantic layer
Create and own the company data dictionary/spine, making it the authoritative source of truth for every data asset, metric definition, and field
Ensure all datasets are tagged, described, and discoverable by both humans and AI systems
Partner with Engineering to embed documentation into data pipelines (dbt, BigQuery, etc.) so it stays current
Structure data assets so they can be consumed by people as well as LLMs and AI agents with minimal prompt engineering overhead
Define the schemas, metadata standards, and retrieval patterns that let AI agents reliably query DeepIntent data
Work directly with Business Intelligence, Revenue Strategy, the Company’s CTO, CEO and AI engineering leads on context architecture for knowledge-dependent workflows.
Partner with teams to help establish and enforce data definitions across functions while resolving definitional conflicts when encountered.
Participate in a lightweight data governance council across Revenue, Product, Engineering, and Data Science
Serve as the internal expert on healthcare and media data standards and their application to advertising use cases