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# Ontologist - Lending Domain (Snowflake & AWS)

- **Company:** GG Tech Global Inc
- **Location:** Atlanta, GA, United States
- **Contract:** Contract
- **Skills:** Training Data, Artificial Intelligence, Amazon Web Services, Data Discovery, Data Governance, Graph Database, Identity and Access Management, Machine Learning, Meta-Data Management, Metadata Repositories, Metadata Standards, Web Ontology Language, SPARQL, Enterprise Data Management, Snowflake, Data Layers, Collibra, Physical Data Models
- **Published:** October 26, 2026
- **Apply:** https://www.dice.com/job-detail/da2306b3-557b-430d-acac-e89279f2fb98

## About the Role

* Strong knowledge of US lending operations, loan lifecycle, underwriting and credit risk.
 * Experience with ontology modeling, semantic technologies, knowledge graphs, and metadata management.
 * Hands-on experience with Snowflake
 * Hands-on experience with AWS services including Neptune, SageMaker, and IAM.
 * Familiarity with RDF, OWL, SPARQL, taxonomy management, and graph databases.
 * Familiarity with FIBO / BIAN
 * Experience supporting AI/ML, data governance, and enterprise data management initiatives.

Preferred Qualifications

 * Experience building AI-ready data products and semantic layers for financial services.
 * Knowledge of graph platforms such as AWS Neptune.
 * Experience with data catalogs such as Alation, Collibra, or similar metadata management tools.

## Description

Looking for Ontologist who will be responsible for designing, developing, and governing business ontologies and semantic models for US lending products, processes, and data assets. This role will work closely with business stakeholders, data architects, and AI teams to establish a common business vocabulary, data relationships, and knowledge graphs that support data products, and AI initiatives., * Develop and maintain lending domain ontologies covering wholesale/commercial, consumer, mortgage, and credit lending.

 * Define business concepts, entities, relationships, and metadata standards across the lifecycle - origination, servicing, underwriting, risk, and collections.
 * Collaborate with business and data teams to align ontology models with enterprise data products and governance frameworks.
 * Enable semantic data discovery, lineage, and AI-ready data assets.
 * Map ontology concepts to physical data models and business data catalogs.