Knowledge Graph Engineer – Entity Resolution & Graph Analytics

3GIMBALS; Virginia (MN); On-site; USD 120,000 - 190,000; Full time

Job summary

3GIMBALS is seeking a Knowledge Graph Engineer to design, build, and maintain a large, multi-source knowledge graph powering an analytic platform. You will model ontologies, implement entity resolution and relationship extraction, and deliver graph-based analytics for connecting people, organizations, locations, events, and other entities across diverse data sources.

The role blends data engineering with semantic modeling and NLP to turn disparate data into a coherent, queryable graph used by

Qualifications

• 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).

Responsibilities

• 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.
• 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.
• 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.
• 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.

Skills

Knowledge graph

Ontology modeling

Python

NLP / information extraction

Entity resolution

Graph databases

Cypher / Gremlin / SPARQL

Data engineering

Tools

Neo4j

Amazon Neptune

JanusGraph

TigerGraph

Docker

Kubernetes

spaCy

Hugging Face

Job 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.