Knowledge Graph Engineer – Entity Resolution & Graph Analytics
3GIMBALS, LLC Virginia, United States
Technology, Information and Internet · 11-50 employees
About the role
The Knowledge Graph Engineer will design, build, and maintain ontologies and graph-based analytic pipelines to integrate heterogeneous data sources. This role involves developing entity resolution techniques, graph queries, and analytics to power discovery within a secure platform.
What they look for
Requirements
Candidates must have at least 4 years of software or data engineering experience with a strong focus on graph databases and semantic modeling. Proficiency in Python and experience with NLP or information extraction techniques are required to succeed in this role.
Full description
Role Overview
3GIMBALS is seeking a Knowledge Graph Engineer to design, build, and maintain the knowledge graph that underpins our unclassified PAI/CAI-based analytic platform. This role is responsible for modeling ontologies, engineering entity resolution and relationship-extraction pipelines, and delivering graph-based analytics that connect people, organizations, locations, events, and other entities across large, heterogeneous data sources. The ideal candidate blends data engineering, semantic modeling, and NLP to turn disparate data into a coherent, queryable graph that powers analytic discovery.
Key Responsibilities
Ontology & Graph Modeling
- Design and evolve ontologies, schemas, and taxonomies for entities and relationships
- Model complex, multi-source data into a coherent, queryable knowledge graph
- Define and maintain graph data standards, naming conventions, and semantics
Entity Resolution & Data Integration
- Build entity resolution, deduplication, and record-linkage pipelines across disparate sources
- Develop relationship and event extraction from structured and unstructured data using NLP / information-extraction techniques
- Integrate curated data from the data engineering team into graph ingestion workflows
- Implement confidence scoring, provenance, and source attribution for graph assertions
Graph Analytics & Query
- Develop graph queries, traversals, and analytics (centrality, community detection, pathfinding, link analysis)
- Expose graph capabilities via APIs and query interfaces for analysts and applications
- Optimize graph storage, indexing, and query performance at scale
Security & Compliance
- Ensure the graph and its interfaces meet security requirements for sensitive environments
- Implement access control, encryption, and secure handling of graph data
- Support Authority to Operate (ATO) processes and compliance frameworks
Required Qualifications
- Technical Expertise
- 4+ years of software or data engineering experience, including hands-on knowledge graph work
- Experience with graph databases (Neo4j, Amazon Neptune, TigerGraph, JanusGraph, or similar)
- Proficiency with graph query languages (Cypher, Gremlin, or SPARQL)
- Strong programming skills in Python (Java or Scala a plus)
- Experience with entity resolution / record-linkage techniques and tooling
- Understanding of ontology and semantic modeling (RDF, OWL, property graphs)
NLP & Data Integration
- Experience with NLP / information extraction (spaCy, Hugging Face, or similar) for entity and relationship extraction
- Experience integrating heterogeneous structured and unstructured data
- Familiarity with vector embeddings and similarity-based linking
Domain Knowledge
- Experience building or maintaining production knowledge graphs
- Understanding of data provenance, confidence, and source attribution
Preferred Qualifications
- Active security clearance or ability to obtain one
- Experience in government, defense, or intelligence contracting environments
- Familiarity with PAI/CAI data sources and entity-centric analysis
- Experience with link analysis and network/graph analytics for investigative use cases
- Knowledge of geospatial-temporal data in a graph context
- Experience integrating knowledge graphs with LLM / RAG systems (GraphRAG)
- Familiarity with federal compliance frameworks (FedRAMP, FISMA, NIST 800-53)
Technical Environment
- Graph: Neo4j / Neptune / JanusGraph; Cypher, Gremlin, SPARQL
- Languages: Python (Java/Scala a plus)
- NLP/ML: spaCy, Hugging Face, embeddings, entity-resolution frameworks
- Data: Integration with platform data pipelines; RDF / property-graph models
- Infrastructure: Docker, Kubernetes, cloud platforms (AWS GovCloud, Azure Government)
- Security: RBAC, encryption, secure APIs
This role owns the connective tissue of the platform: the ontology and graph that let analysts move from isolated records to the relationships, networks, and patterns that drive insight.