Senior Ontologist (Data modeling, Snowflake/AWS)

Hybrid in Charlotte, NC, US • Posted 9 hours ago • Updated 9 hours ago
Contract Corp To Corp
Contract W2
Contract Independent
12 Months
No Travel Required
Hybrid
$75/hr
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Data Architecture
  • Business Process
  • Collaboration
  • Computer Science
  • Analytical Skill
  • Artificial Intelligence
  • Banking
  • Amazon Neptune
  • Amazon SageMaker
  • Amazon Web Services
  • Data Modeling
  • Data Quality
  • Data Science
  • Data Engineering
  • Data Governance
  • Data Management
  • Collections
  • Conflict Resolution
  • Credit Risk

Summary

Location: Atlanta(GA), Charlotte (NC), Raleigh (NC) 

Day-to-Day Job Duties: (What this person will do on a daily/weekly basis)

  • Design, develop, and maintain business ontologies and semantic models for US lending products, processes, and enterprise data assets.
  • Define business concepts, entities, relationships, taxonomies, and metadata standards across commercial, wholesale, consumer, mortgage, and credit lending.
  • Model the end-to-end lending lifecycle, including loan origination, underwriting, servicing, credit risk, and collections.
  • Collaborate with business stakeholders, data architects, data engineers, governance teams, and AI/ML teams to align semantic models with enterprise data products.
  • Map ontology concepts and relationships to physical data models, Snowflake data assets, and enterprise data catalogs.
  • Develop and maintain knowledge graphs and semantic layers to support data discovery, lineage, integration, and AI-enabled use cases.
  • Leverage AWS services, including Amazon Neptune, SageMaker, and IAM, to support graph modeling, AI/ML initiatives, and secure data access.
  • Apply semantic technologies and standards such as RDF, OWL, and SPARQL to develop and manage ontology models.
  • Establish ontology governance, naming conventions, metadata standards, and reusable modeling practices.
  • Support data governance, data quality, metadata management, and enterprise data management initiatives.
  • Partner with AI/ML teams to enable AI-ready data assets, semantic search, knowledge graph applications, and data-driven solutions.
  • Evaluate and improve ontology models based on evolving business requirements, data architecture, regulatory needs, and enterprise standards.

Basic Qualifications: (What are the skills required for this job with minimum years of experience on each)

  • Minimum 7+ years of experience in data modeling, semantic modeling, ontology engineering, knowledge management, or enterprise data architecture.
  • Minimum 5+ years of experience in ontology modeling, semantic technologies, knowledge graphs, or taxonomy management.
  • Minimum 5+ years of experience in Banking, Financial Services, or lending-related data and business processes.
  • Minimum 3+ years of experience with US lending products, including loan origination, underwriting, servicing, credit risk, or collections.
  • Minimum 3+ years of hands-on experience with Snowflake and enterprise data environments.
  • Minimum 2+ years of experience working with AWS services, preferably Amazon Neptune, SageMaker, and IAM.
  • Strong understanding of RDF, OWL, SPARQL, graph databases, metadata management, and semantic data modeling.
  • Experience mapping business concepts and ontologies to physical data models, data catalogs, and enterprise data products.
  • Experience supporting AI/ML, data governance, data quality, and enterprise data management initiatives.
  • Strong analytical, problem-solving, documentation, and stakeholder collaboration skills.
  • Ability to translate complex lending concepts into reusable semantic models and business-friendly terminology.

Degree:

Bachelor’s degree in Computer Science, Information Technology, Data Science, Engineering, or a related field, or equivalent professional experience.

Nice to Have:

  • Experience with FIBO (Financial Industry Business Ontology) or BIAN (Banking Industry Architecture Network).
  • Experience building AI-ready data products, semantic layers, and knowledge graph solutions for financial services.
  • Hands-on experience with Amazon Neptune or other graph database platforms.
  • Experience with Alation, Collibra, or similar enterprise data catalog and metadata management tools.
  • Knowledge of regulatory reporting, data lineage, data governance, and financial services data standards.
  • Experience collaborating with data engineering, enterprise architecture, and AI/ML teams on large-scale data initiatives.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10299481
  • Position Id: 9126373
  • Posted 9 hours ago
Contact the job poster
KM

Kishan Mishra

Lead Recruiter @ McKinsol Consulting Inc

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