Graph Data Engineer — Semantic Knowledge Graph (TS/SCI)

Redhorse Corporation; Virginia (MN); On-site; USD 140,000 - 170,000; Full time

Job summary

Redhorse Corporation seeks a Graph Data Engineer to design, build, scale, and maintain the Enterprise Semantic Map, an ontology-grounded metadata graph. You will lead automation-first data ingestion, API integrations, and lineage tracking to ensure data is discoverable and trustworthy for analysts and AI agents.

You will work with graph, data, and engineering teams, applying systems thinking to align assets to enterprise semantics while mentoring junior engineers and documenting design decisions

Qualifications

• Bachelor’s Degree with 5+ years of relevant professional experience
• Active TS SCI Clearance
• Foundational skills in Python/Java and SQL
• Experience building production data pipelines/ETL
• Hands-on with enterprise graph databases
• APIs and systems integration experience
• Systems-thinking mindset and attention to detail
• Strong communication with stakeholders

Responsibilities

• Design, build, and deploy automated pipelines that discover enterprise data assets and interface with data catalogs
• Ingest, catalog, and manage technical metadata (schemas, tables, APIs) from diverse environments
• Define data lineage and provenance tracking across ingestion points
• Align discovered data elements to Enterprise Core Ontology and domain ontologies
• Collaborate with graph, data, and engineering teams to enable downstream AI agents
• Mentor junior engineers and document schema decisions and runbooks

Skills

Python

Java

SQL

Knowledge graph concepts

APIs

Data pipelines

Systems thinking

Attention to detail

Communication

Education

Bachelor’s Degree

Tools

Cypher

SPARQL

Graph databases

Job description

Redhorse Corporation seeks a Graph Data Engineer to design, build, scale, and maintain the Enterprise Semantic Map, an ontology-grounded metadata graph. You will lead automation-first data ingestion, API integrations, and lineage tracking to ensure data is discoverable and trustworthy for analysts and AI agents.

You will work with graph, data, and engineering teams, applying systems thinking to align assets to enterprise semantics while mentoring junior engineers and documenting design decisions