Principal Software Engineer​/Data Engineer; Onsite

Date Posted:  Country:
United States of America

Location:

US-TX-RICHARDSON-C17 ~ 1717 Cityline Dr ~ CITYLINE C17 Position Role Type:
Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements:
Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: TS/SCI - Current Security Clearance Status:
Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can.

Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today’s mission and stay ahead of tomorrow’s threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world.

Join us and help shape the future of aerospace and defense.

RTX is seeking a Data Engineer for an immediate position onsite in our Richardson, TX or Dulles, VA office.

The Data Engineer will be a key contributor to our program, responsible for designing semantic data models, ontologies, and knowledge graphs that serve as the connective tissue between raw operational data and AI-ready intelligence.

• Design, build, and maintain enterprise ontologies and knowledge graphs using standards such as OWL, RDF, and SPARQL.
• Collaborate with domain experts, data engineers, and business stakeholders to capture and formalize business concepts, relationships, and rules.
• Develop and manage taxonomies, controlled vocabularies, and semantic metadata schemas across operational and business domains.
• Integrate ontological structures with enterprise data platforms, AI/ML pipelines, and analytics environments.
• Partner with AI/ML Engineers and data scientists to ensure ontology structures support downstream model training, feature engineering, and inference pipelines.
• Define and enforce data governance standards for entity definitions, lineage tracking, and metadata management across enterprise platforms.
• Monitor ontology performance and usage patterns; proactively identify gaps and drive continuous improvement.
• Support integration of ontology layers with enterprise data products, dashboards, and reporting tools.
• Evaluate and implement ontology management tools and platforms, ensuring scalability and interoperability.
• Translate complex technical concepts into clear documentation for both technical and non-technical audiences.
• Stay current with advancements in knowledge representation, semantic web technologies, and AI/ML techniques.

Typically requires a degree in Science, Technology, Engineering or Mathematics (STEM) and 8 years of relevant experience.

• Experience in using OWL, RDF, RDFS, SPARQL, and related W3C semantic web standards.
• Experience with ontology development tools such as Protégé, Top Braid Composer, or similar.
• Experience in developing conceptual, logical, and physical data models, as well as canonical data designs.
• Experience with graph databases (e.g., Stardog, Neo4j, Amazon Neptune, Azure Cosmos DB for Gremlin) and graph query languages.
• Experience collaborating in cross-functional Agile or Dev Ops environments.
• Active and transferable TS/SCI U.S. government issued security clearance is required prior to start date.
• U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance.

• Experience with data fabric, data mesh, Lakehouse architectures, and cloud platforms (Azure, AWS).
• Background supporting digital thread, digital twin, and AI/ML programs.
• Experience mentoring or leading data modeling teams.
• Knowledge of linked data principles and experience publishing or consuming linked datasets.
• E…