Senior Data Engineer - Knowledge Graphs

About PeratonPeraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees solve the most daunting challenges that our customers face. Visit peraton.com to learn how we're keeping people around the world safe and secure.About The RolePeraton Labs is seeking a Senior Data Engineer to help design, build, and operationalize the data foundations supporting advanced AI-enabled capabilities. This role will focus on transforming complex structured and unstructured information into graph-aware, semantically meaningful data products that can support analytics, reasoning, retrieval, and agentic workflows.We are looking for a candidate who combines strong data engineering execution with meaningful experience in knowledge graphs, semantic representations, NLP-derived structure, and graph-based analysis. This may come from a traditional data engineering background with hands-on knowledge graph experience, or from a research-oriented knowledge graph / semantic systems background paired with proven implementation ability.The ideal candidate for this role should be comfortable working across data pipelines, semantic modeling, graph representations, and AI-enabled data architectures. You should be comfortable moving between concept and implementation, helping shape how knowledge is extracted, structured, linked, and made usable for downstream AI systems.Key responsibilities may include, but are not limited to:Design, build, and maintain scalable data pipelines supporting graph-based and AI-enabled workflowsDevelop data models and processing approaches that transform raw structured and unstructured data into semantically meaningful graph-oriented representationsContribute to the creation, enrichment, and operationalization of knowledge graphs supporting retrieval, reasoning, entity relationships, and advanced analyticsSupport ingestion, normalization, linking, and transformation of data into graph-compatible formats such as RDF and related semantic representationsApply experience in areas such as NLP, AMR, UMR, semantic parsing, graph analysis, or ontology-informed data modeling to improve how information is structured and connectedBuild data pipelines and engineering workflows that support graph-centric applications, including AI-enabled search, contextual retrieval, and decision supportPartner with AI/ML, platform, and software engineering teams to ensure graph and semantic data assets are usable within production-oriented systemsHelp define approaches for entity resolution, relationship extraction, semantic enrichment, metadata management, and graph quality validationContribute to architectures that support agentic AI workflows by enabling richer data context, structured memory, and relationship-aware information accessWork with a mix of structured, semi-structured, and unstructured data sources to improve interoperability and downstream usabilitySupport graph analysis and exploration efforts that inform system design, data relationships, and capability developmentEnsure data engineering solutions are maintainable, scalable, and aligned to operational and mission needsDocument data flows, graph models, transformation logic, and engineering decisions clearly for technical stakeholdersQualificationsRequired QualificationsMinimum of BS with 12+ years of experience, MS with 10+ YoE, or PhD with 7+ YoE in data engineering, knowledge graph engineering, semantic systems, NLP-enabled data processing, or related technical rolesStrong hands-on experience building and maintaining data pipelines in modern engineering environmentsDemonstrated experience with knowledge graphs, graph data models, or semantic data architecturesExperience within one or more of the following areas: RDF, graph analysis, semantic representation, ontology-informed data modeling, AMR, UMR, or NLP-driven structured extractionStrong hands-on experience with Python, JavaScript/TypeScript, and SQL for data transformation and pipeline development, plus familiarity with graph and semantic tooling such as Neo4j/Neptune/GraphDB platformsExperience working with both structured and unstructured data in support of downstream analytics or AI/ML use casesAbility to translate complex source data into usable, high-quality representations for graph-based or semantic systemsStrong understanding of data quality, schema design, metadata, transformation logic, and scalable data workflowsAbility to operate effectively in highly technical environments where requirements may evolve and where both rigor and adaptability matterStrong written and verbal communication skills, with the ability to explain technical tradeoffs clearly across engineering and non-engineering stakeholdersUS Citizenship is a requirement for this positionPreferred QualificationsExperience with agentic AI systems or workflows that rely on structured context, memory, planning, or relationship-aware retrievalExperience with GraphRAG or related graph-enhanced retrieval architecturesFamiliarity with graph databases, triplestores, semantic query languages, or related toolingExperience supporting entity resolution, relationship extraction, semantic search, or contextual retrieval workflowsBackground in NLP, semantic parsing, knowledge representation, or computational linguisticsExperience designing systems that connect knowledge representation approaches to operational AI applicationsFamiliarity with ontology development, schema alignment, or semantic interoperability challengesExposure to mission, government, defense, or regulated technical environmentsAdvanced degree in computer science, data science, computational linguistics, AI/ML, or a related fieldDetailsTarget Salary Range: $135,000 - $216,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual's experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.Benefits Statement: Peraton offers eligible employees a variety of benefits including medical, dental, vision, life, health savings account, short/long term disability, EAP, parental leave, 401(k), paid time off (PTO) for vacation, and company paid holidays. A full listing of available benefits can be viewed at https://www.careers.peraton.com/benefits.Application Duration Statement: The application period for the job is estimated to be 30 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates.EEO:Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.