- Redhorsecorp
- Arlington, TX
- Full-Time
- 25 days ago
- $85,000 – $105,000
Junior Graph Data Engineer.
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Junior Graph Data Engineer: our view in 3 lines...
- The Role:This role is for a junior data engineer building and maintaining an enterprise semantic map using graph analytics and automation.
- The Person:The person will build and maintain the Enterprise Semantic Map, develop data and API integrations, configure graph database structures, and support workflows that discover and catalog enterprise data sources.
- Requirements:The role calls for foundational coding skills and a systems-thinking mindset, with graph analytics, artificial intelligence, graph technologies, and agile delivery mentioned in the description.
About the role
Now is an exciting time to join Redhorse Corporation.
We are redefining how the U.S. Government transforms data into operational advantage through artificial intelligence, graph analytics, and mission-driven software engineering. Our teams work alongside the Department of Defense to build secure, scalable capabilities that enable analysts and decision-makers to move faster, reason better, and operate with greater confidence.
Our approach combines human-centered design, modern software engineering, graph technologies, artificial intelligence, and agile delivery to solve some of the nation’s most challenging problems.
About the Role
We are seeking an analytical, forward-thinking Junior Graph Data Engineer to help build, scale, and maintain the Enterprise Semantic Map — our ontology-grounded metadata graph.
In this role, you will help move the enterprise beyond traditional, static cataloging by supporting an automation-first approach. You will develop programmatic data and API integrations, help configure graph database structures, and support emerging agentic workflows that discover and catalog disparate data sources across the enterprise. Working alongside graph, data, and engineering teams, you will help align these assets to enterprise semantic and provenance layers so data is discoverable, understandable, trusted, and dynamically composable for human analysts, applications, and downstream AI agents.
Success in this role requires foundational coding skills and a systems-thinking mindset: an ability to understand how data pipelines and tool integrations affect the broader enterprise architecture, search and discovery, and downstream agentic research workflows and use cases.
