Graph Data Engineer

Now is a great time to join Redhorse Corporation. We are a solution-driven company delivering data insights and technology solutions to customers with missions critical to U.S. national interests. We’re looking for thoughtful, skilled professionals who thrive as trusted partners building technology-agnostic solutions and want to apply their talents supporting customers with difficult and important mission sets.

About the Role

Redhorse transforms the way government uses data and technology. We are seeking a Data Engineer to support a cross-functional team building technology-enabled, mission-critical intelligence workflows. Most intelligence transformation technologies fail because they are disconnected from how analysts think and act under pressure—our team works to prevent that.

Working in close partnership with graph data scientists and other engineers, you will ensure our state-of-the-art analytic platform (GraphAware Hume) supports real-world operational tradecraft. This is not a role focused on producing intelligence products; it is a role focused on building the pipelines and systems that produce decision advantage. You will play a vital part in ensuring the analytics platform answers complex queries and results in a user experience that delights analysts and survives contact with reality.

• Design, build, and maintain robust data ingestion and transformation pipelines that supply the knowledge graph analytics platform.
• Profile source data and assess structure, quality, completeness, and integration challenges.
• Implement complex transformation, normalization, and preparation logic required to load data into graph solutions.
• Support source-to-graph traceability and data lineage to ensure analytic transparency and rapid debugging.
• Collaborate with the Lead Data Scientist and engineering peers to align source data processing with graph modeling and entity resolution requirements.
• Continuously improve data quality handling and pipeline reliability to ensure high-availability of intelligence insights.
• Document ingestion patterns, transformation rules, and technical considerations to support enterprise scaling.
• Utilize Jira and GitLab to manage tasks and maintain version control across the development lifecycle.

• 5+ years of relevant professional experience in data engineering or related technical roles.
• Demonstrated experience in ETL/ELT development and large-scale data integration.
• Proven ability to handle both structured and semi-structured data from multiple disparate source systems.
• Experience designing transformation logic that supports downstream analytics, graph loading, and operational traceability.
• Proficiency with scripting (e.g., Python), data processing frameworks, and production-minded engineering practices.
• Bachelor’s degree from an accredited institution in Computer Science, Engineering, Information Systems, Mathematics, or a related field.

We encourage all candidates who meet the basic requirements to apply, even if you do not have any of the following experience:

• Experience supporting analytics, graph platforms (like Neo4j), or complex investigative data environments.
• Familiarity with DataBricks or Apache Spark for large-scale data processing.
• Knowledge of GraphAware Hume or other knowledge graph orchestration tools.
• Experience with CI/CD pipelines and automated testing for data workflows.
• Active security clearance or the ability to undergo a background investigation for government-related work.