
Senior Ontologist (Lending Domain / Snowflake / AWS)
Atlanta, GAContract$80–90/hrSeen todaySeen in employer's feed today
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Job overview
NTT DATA is seeking a Senior Ontologist to design and maintain semantic models for U.S. lending products and enterprise data assets. The role works across lending processes, data architecture, governance, and AI/ML initiatives, using Snowflake, AWS services, and semantic technologies. The position also supports knowledge graphs, data catalogs, ontology governance, and AI-ready data products.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
Company Overview:
Req ID: 395526
NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.
We are currently seeking a Senior Ontologist (Lending Domain / Snowflake / AWS) to join our team in Charlotte, North Carolina (US-NC), United States (US).
Job Description Senior Ontologist (Lending Domain / Snowflake / AWS)
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.
Travel:
As required by business needs.
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.
#LI-NorthAmerica
NTT DATA provides a reasonable range of compensation for U.S.-based positions. The starting pay range for this role is [80 - 90$ W2 hourly range]. Actual compensation will depend on a number of factors, including the candidate's relevant experience, technical skills, and other qualifications. This position is eligible for company benefits including participation in medical, dental, and vision insurance, flexible spending or health savings account, and AD&D insurance, employee assistance, participation in a 401k program, and additional voluntary or legally-required benefits.
About NTT DATA:
NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at us.nttdata.com
NTT DATA endeavors to make https://us.nttdata.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at https://us.nttdata.com/en/contact-us. This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here. For Pay Transparency information, please click here.
How this job compares
Set against the 1,377 open Data Architect jobs on Olive Jobs, counted October 27, 2026.
- Pay
- This posting$80–90/hr
- US median$70–86/hr22 hourly ranges
This range's midpoint, $85/hr, is 8% above the US median midpoint ($79/hr) — in the middle half of Data Architect hourly ranges across the US.
- Openings
- Olive Jobs lists 28 open Data Architect jobs in Georgia and 1,377 across the US. 14% of them nationwide are listed as remote or flexible.
- Hiring the most in Georgia
- Accenture5 open
- Warner Bros. Discovery3 open
- Amazon2 open
- Experience
- This posting asks for at least 7 years of experience; Data Architect postings that state a minimum ask for 8 years at the median (1,238 postings).
- Education
- 520 of the 1,377 open Data Architect jobs (38%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on October 27, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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