Design, build, and maintain ingestion and transformation pipelines for a knowledge-graph analytics platform. Profile and prepare structured and semi-structured source data, ensure data lineage and traceability, implement transformation logic for graph loading, collaborate with data scientists on graph modeling and entity resolution, improve pipeline reliability, and document ingestion patterns using version control and issue tracking.
About the Organization
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.
Key Responsibilities
- 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.
Required Experience/Clearance
- 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.
Desired 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.
We encourage all candidates who meet the basic requirements to apply, even if you do not have any of the following experience:
The salary range provided for this position represents the anticipated base salary for successful candidates. Actual compensation will be determined based on a variety of factors, including relevant experience, education, certifications, skills, security clearance level, geographic location, market conditions, and internal equity. In addition to base salary, eligible employees may participate in Redhorse's comprehensive benefits programs and may be eligible for performance-based or other incentive compensation, where applicable.
Redhorse Corporation is an equal opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability, or any other protected class.
If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to access job openings or apply for a job on this site as a result of your disability. You can request reasonable accommodations by contacting Talent Acquisition at [email protected]
Redhorse Corporation shall, in its discretion, modify or adjust the position to meet Redhorse’s changing needs. This job description is not a contract and may be adjusted as deemed appropriate in Redhorse’s sole discretion.
Similar Jobs
Artificial Intelligence • Big Data • Cloud • Information Technology • Software • Big Data Analytics • Automation
Provide technical sales support for Dynatrace observability products: deliver demos, manage onsite/remote POCs, respond to RFIs/RFPs, advise on cloud architecture, present to executives, collaborate with sales, partners, services, and product teams, and gather customer feedback. Role requires travel and cross-functional coordination.
Top Skills:
.NetAnsibleAWSAzureCi/CdContainersCSSDatabaseDynatraceGCPGoHTMLJavaJavaScriptKubernetesLinuxNode.jsOpenshiftPHPPuppetServerlessTerraformWindows
Artificial Intelligence • Big Data • Cloud • Information Technology • Software • Big Data Analytics • Automation
Serve as a strategic HR Business Partner for Americas Sales and Marketing, advising senior leaders on talent planning, org design, compensation, performance enablement, and change initiatives. Use workforce data to align people strategies with business metrics, support onboarding, retention, and leadership development, ensure regional compliance, and collaborate with Centers of Excellence and HR teams to drive scalable, high-impact GTM people programs.
Artificial Intelligence • Big Data • Cloud • Information Technology • Software • Big Data Analytics • Automation
Own and optimize the end-to-end marketing technology stack: roadmap, tool selection, implementations, integrations, documentation, governance, and performance metrics. Partner with IT, Sales Ops, Analytics, and Legal to ensure data flows, adoption, and ROI while supporting onboarding and ongoing optimization.
Top Skills:
6SenseAPIsLeandataMarketoPower BISalesforce
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
