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HomeCompaniesCareers Gdms Icims ComData Ontology Engineer

Data Ontology Engineer

Careers Gdms Icims Com · UNAVAILABLE, UNAVAILABLE, US · Remote · Active · $142,696–$158,303 / hour · iCIMS

Job facts

FieldValue
CompanyCareers Gdms Icims Com
TitleData Ontology Engineer
Normalized title-
Department / teamEngineering-Systems
LocationUNAVAILABLE, UNAVAILABLE, United States
Work modelRemote / Remote
Employment typeOTHER
Salary$142,696–$158,303 / hour
Statusactive
ATS provideriCIMS
Posted / first seen2026-06-02 / 2026-06-03
Changed / last seen2026-06-13 / 2026-06-20

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PageWhat it containsOpen
Company jobsActive postings from Careers Gdms Icims Com.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
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Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in UNAVAILABLE.Open
Department jobsActive postings in Engineering-Systems.Open
Work model jobsActive Remote postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyCareers Gdms Icims Com
Source50a48765-ecd2-4cf1-922c-f51ba44a14f5
ATS provideriCIMS

Description

Basic Qualifications Bachelor's degree in Systems Engineering, or a related Science, Engineering or Mathematics field, plus a minimum of 8 years of relevant experience; or Master's degree, plus a minimum of 6 years of relevant experience. CLEARANCE REQUIREMENTS: : Department of Defense Secret security clearance is required at time of hire. Applicants selected will be subject to a U.S. Government security investigation and must meet eligibility requirements for access to classified information. Due to the nature of work performed within our facilities, U.S. citizenship is required. Responsibilities for this Position What You'll Own Domain ontologies. Design and maintain semantic schemas that describe key engineering and manufacturing entities — products, BOMs, plants, equipment, processes, work orders — and their relationships across systems. Knowledge graphs. Implement ontologies using semantic web or graph technologies (RDF/OWL/SHACL/SPARQL or property-graph equivalents like Neo4j). Build, query, validate, and tune knowledge graphs in production. Data alignment. Integrate heterogeneous data sources — PLM, ERP, MES, CMMS, QMS, data lakes — into a common vocabulary. Align schemas, code sets, and master data to the ontology so AI services see one coherent picture. Semantic layer. Design the enterprise semantic layer that BI tools, analytics platforms, and AI/LLM applications query consistently. Define core business entities, metrics, and hierarchies and map them to existing data stores. Ontology governance. Manage versioning, documentation, reuse of industry standards, and enforcement of modeling best practices across pods. Your ontologies are shared assets — they must be maintainable by others. What You Won't Own AI model development or prompt engineering — you provide the data substrate, the AI engineers build on it Enterprise system administration — you integrate data from systems, you don't manage them Business process decisions — Domain SMEs and the Product Owner define what matters; you model it What Makes This Role Different Your ontologies directly feed AI systems that make real business decisions. A bad data model doesn't just slow a report — it makes an AI agent reason incorrectly. You will work across multiple enterprise domains — HR, manufacturing, CRM, supply chain — building a shared knowledge architecture, not siloed data models. You will collaborate with business SMEs who understand the domain and AI engineers who consume your models. You translate between both worlds. Required Qualifications Bachelor’s degree in Computer Science, Data Science, Information Science, or a related field, plus 5 years of experience; or Master’s degree plus 3 years of experience Hands-on experience with knowledge graph or ontology technologies — RDF/OWL/SHACL/SKOS, SPARQL, and/or graph databases (Neo4j, Stardog, Ontotext, AWS Neptune, or similar) Experience integrating disparate enterprise data sources into a shared vocabulary or knowledge graph — you have aligned data across systems that use different schemas, code sets, and terminology Strong data modeling skills — dimensional modeling, semantic modeling, or formal ontology design applied in production, not just academic settings Experience with enterprise data platforms — data warehouses, data lakes, Snowflake, Palantir Foundry, or similar U.S. citizenship required. Department of Defense Secret security clearance is required at time of hire. Preferred Qualifications Experience building semantic layers or metrics layers consumed by BI, analytics, or AI/LLM applications Experience with enterprise systems data (ERP, MES, PLM, CRM) — you understand the data structures these systems produce Familiarity with AI/ML data requirements — embeddings, vectorization, retrieval-augmented generation, and how knowledge graphs support LLM reasoning Comfortable leading workshops with non-technical business SMEs to capture requirements and iteratively refine data models Experience with ontology governance — versioning, documentation, standards reuse across teams or an enterprise What Sets You Apart You think in relationships, not rows. You see connections between data that others model as flat tables. You can explain a semantic model to a business SME and have them recognize their domain in it. You build ontologies that other people can use and extend — not elegant models that only you understand. You have integrated data from systems that were never designed to work together and made it coherent. You care about data meaning, not just data structure. You know that two systems calling something "part number" doesn't mean they mean the same thing. Details Remote — 100% telework 9/80 schedule Defense industry experience is not required Salary Note This estimate represents the typical salary range for this position based on experience and other factors (geographic location, etc.). Actual pay may vary. This job posting will remain open until the position is filled. Combined Salary Range USD $142,696.00 - USD $158,303.00 /Yr. Company Overview General Dynamics Mission Systems (GDMS) engineers a diverse portfolio of high technology solutions, products and services that enable customers to successfully execute missions across all domains of operation. With a global team of 12,000+ top professionals, we partner with the best in industry to expand the bounds of innovation in the defense and scientific arenas. Given the nature of our work and who we are, we value trust, honesty, alignment and transparency. We offer highly competitive benefits and pride ourselves in being a great place to work with a shared sense of purpose. You will also enjoy a flexible work environment where contributions are recognized and rewarded. If who we are and what we do resonates with you, we invite you to join our high-performance team! Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

Full job record

Job ID51bf1177df4651071f43fc3f5e794b9e02f0eb94
Org IDe6402653-8a5c-4195-a6aa-6434d4616247
Source ID50a48765-ecd2-4cf1-922c-f51ba44a14f5
Board ID50a48765-ecd2-4cf1-922c-f51ba44a14f5
Providericims
Provider Job Key72874
TitleData Ontology Engineer
Normalized Title
Statusactive
Activeyes
Location TextUNAVAILABLE, UNAVAILABLE, US
DepartmentEngineering-Systems
Team
Employment TypeOTHER
Workplace Typeremote
Remote Policyremote
CountryUnited States
RegionUNAVAILABLE
CityUNAVAILABLE
Salary RawBasic Qualifications Bachelor's degree in Systems Engineering, or a related Science, Engineering or Mathematics field, plus a minimum of 8 years of relevant experience; or Master's degree, plus a minimum of 6 years of relevant experience. CLEARANCE REQUIREMENTS: : Department of Defense Secret security clearance is required at time of hire. Applicants selected will be subject to a U.S. Government security investigation and must meet eligibility requirements for access to classified information. Due to the nature of work performed within our facilities, U.S. citizenship is required. Responsibilities for this Position What You'll Own Domain ontologies. Design and maintain semantic schemas that describe key engineering and manufacturing entities — products, BOMs, plants, equipment, processes, work orders — and their relationships across systems. Knowledge graphs. Implement ontologies using semantic web or graph technologies (RDF/OWL/SHACL/SPARQL or property-graph equivalents like Neo4j). Build, query, validate, and tune knowledge graphs in production. Data alignment. Integrate heterogeneous data sources — PLM, ERP, MES, CMMS, QMS, data lakes — into a common vocabulary. Align schemas, code sets, and master data to the ontology so AI services see one coherent picture. Semantic layer. Design the enterprise semantic layer that BI tools, analytics platforms, and AI/LLM applications query consistently. Define core business entities, metrics, and hierarchies and map them to existing data stores. Ontology governance. Manage versioning, documentation, reuse of industry standards, and enforcement of modeling best practices across pods. Your ontologies are shared assets — they must be maintainable by others. What You Won't Own AI model development or prompt engineering — you provide the data substrate, the AI engineers build on it Enterprise system administration — you integrate data from systems, you don't manage them Business process decisions — Domain SMEs and the Product Owner define what matters; you model it What Makes This Role Different Your ontologies directly feed AI systems that make real business decisions. A bad data model doesn't just slow a report — it makes an AI agent reason incorrectly. You will work across multiple enterprise domains — HR, manufacturing, CRM, supply chain — building a shared knowledge architecture, not siloed data models. You will collaborate with business SMEs who understand the domain and AI engineers who consume your models. You translate between both worlds. Required Qualifications Bachelor’s degree in Computer Science, Data Science, Information Science, or a related field, plus 5 years of experience; or Master’s degree plus 3 years of experience Hands-on experience with knowledge graph or ontology technologies — RDF/OWL/SHACL/SKOS, SPARQL, and/or graph databases (Neo4j, Stardog, Ontotext, AWS Neptune, or similar) Experience integrating disparate enterprise data sources into a shared vocabulary or knowledge graph — you have aligned data across systems that use different schemas, code sets, and terminology Strong data modeling skills — dimensional modeling, semantic modeling, or formal ontology design applied in production, not just academic settings Experience with enterprise data platforms — data warehouses, data lakes, Snowflake, Palantir Foundry, or similar U.S. citizenship required. Department of Defense Secret security clearance is required at time of hire. Preferred Qualifications Experience building semantic layers or metrics layers consumed by BI, analytics, or AI/LLM applications Experience with enterprise systems data (ERP, MES, PLM, CRM) — you understand the data structures these systems produce Familiarity with AI/ML data requirements — embeddings, vectorization, retrieval-augmented generation, and how knowledge graphs support LLM reasoning Comfortable leading workshops with non-technical business SMEs to capture requirements and iteratively refine data models Experience with ontology governance — versioning, documentation, standards reuse across teams or an enterprise What Sets You Apart You think in relationships, not rows. You see connections between data that others model as flat tables. You can explain a semantic model to a business SME and have them recognize their domain in it. You build ontologies that other people can use and extend — not elegant models that only you understand. You have integrated data from systems that were never designed to work together and made it coherent. You care about data meaning, not just data structure. You know that two systems calling something "part number" doesn't mean they mean the same thing. Details Remote — 100% telework 9/80 schedule Defense industry experience is not required Salary Note This estimate represents the typical salary range for this position based on experience and other factors (geographic location, etc.). Actual pay may vary. This job posting will remain open until the position is filled. Combined Salary Range USD $142,696.00 - USD $158,303.00 /Yr. Company Overview General Dynamics Mission Systems (GDMS) engineers a diverse portfolio of high technology solutions, products and services that enable customers to successfully execute missions across all domains of operation. With a global team of 12,000+ top professionals, we partner with the best in industry to expand the bounds of innovation in the defense and scientific arenas. Given the nature of our work and who we are, we value trust, honesty, alignment and transparency. We offer highly competitive benefits and pride ourselves in being a great place to work with a shared sense of purpose. You will also enjoy a flexible work environment where contributions are recognized and rewarded. If who we are and what we do resonates with you, we invite you to join our high-performance team! Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans
Salary Min142,696
Salary Max158,303
Salary CurrencyUSD
Salary Periodhour
Source URLhttps://careers-gdms.icims.com/jobs/72874/data-ontology-engineer/job
Apply URLhttps://careers-gdms.icims.com/jobs/72874/data-ontology-engineer/job
First Seen At2026-06-03 14:06:07Z
Last Seen At2026-06-20 08:26:58Z
Last Checked At2026-06-20 08:26:58Z
Last Changed At2026-06-13 08:21:59Z
Inactive At
Source Posted At2026-06-02 04:00:00Z
Source Updated At2026-06-12 16:58:18Z
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