Junior Graph Data Engineer with TS/SCI Clearance

Redhorse Corporation; Arlington (VA); On-site; USD 85,000 - 105,000; Full time

Job summary

Redhorse Corporation in Arlington, VA seeks a Junior Graph Data Engineer to help build and scale the Enterprise Semantic Map—an ontology-grounded metadata graph. You will support automation-first data discovery, programmatic data and API integrations, and configure graph structures for enterprise use.

Working with graph, data, and engineering teams, you will align assets to enterprise semantic and provenance layers so data is discoverable, understandable, and trustworthy for analysts and AI

Qualifications

• Bachelor’s degree with 1+ year of professional experience or equivalent.
• Active TS SCI Clearance.
• Proficiency in programming/scripting for automation (Python/Java).
• Relational database querying (SQL).
• Knowledge graph concepts and metadata schemas.
• Foundational data engineering and ETL understanding.
• Systems-thinking mindset and attention to detail.
• Strong collaboration and communication skills.

Responsibilities

• Automated Source Discovery & Metadata Ingestion: design and deploy pipelines to discover data assets and ingest technical metadata.
• Scale the Semantic Map with automated pipelines to handle metadata at scale.
• Establish data lineage by registering data origins at ingestion.

Skills

Python/Java scripting

SQL queries

Knowledge graph concepts

Data engineering basics

Systems thinking

Attention to detail

Collaboration & communication

Education

Bachelor’s Degree

Tools

Graph databases

Cypher/ SPARQL familiarity

Job description

Redhorse Corporation in Arlington, VA seeks a Junior Graph Data Engineer to help build and scale the Enterprise Semantic Map—an ontology-grounded metadata graph. You will support automation-first data discovery, programmatic data and API integrations, and configure graph structures for enterprise use.

Working with graph, data, and engineering teams, you will align assets to enterprise semantic and provenance layers so data is discoverable, understandable, and trustworthy for analysts and AI