Design and optimize to efficiently manage large-scale hierarchical classification structures, ensuring high-performance search, aggregation, and update operations.
Design, implement, and maintain a supporting hierarchical graph structures optimized for large, dense batch updates and high-throughput analytics.
Develop scalable ingestion pipelines that support scalable graph analytics.
Design data schemas, indexing strategies, and partitioning approaches to maximize query performance, scalability, and storage efficiency.
Collaborate with infrastructure and platform engineering teams to deploy, operate, and optimize Elasticsearch and graph database services in a environment using cloud-native technologies.
Partner with Data Scientists and AI/ML engineers to ingest, curate, manage, analyze, and securely expunge datasets throughout the data lifecycle.
Develop automated data loading, transformation, validation, and quality assurance pipelines supporting production analytics workflows.
Optimize graph and search infrastructure for high availability, resilience, and performance under large-scale analytical workloads.
Collaborate with software engineers and system architects to integrate graph and search services into microservice-based applications.
Participate in SAFe Agile development activities, including sprint planning, design reviews, architecture discussions, and technical demonstrations.
Foster a culture of innovation, collaboration, and professional development within the team.
Ensure sound engineering practices, compliance with policies, and delivery of high-quality software.
Coordinate with test teams to develop and monitor automated system integration tests.
Engage with cross-functional teams to identify and develop high-value integrations with other systems/applications.
Provide specific input to the software components of system design to include hardware/software trade-offs, software reuse, use of

COTS/GOTS

in place of new development, and requirements analysis and synthesis from system level to individual software components.

Bachelor's degree in Computer Science, Data Engineering, or related field and 12-15 years of relevant experience, or Master's with 10-13 years of experience.
Must possess an Active Top Secret/SCI clearance and ability to obtain and maintain a Polygraph.
Elasticsearch/OpenSearch architecture, index design, mappings, analyzers, and query optimization.
Graph databases such as .
Data modeling for hierarchical and highly connected datasets.
Large-scale ETL/ELT pipeline development.
Kubernetes deployment and operations for stateful data services.
Distributed storage systems and high-volume data ingestion.
Python or Java for data engineering and automation.
Experience supporting AI/ML and data science workflows. Apache Kafka or similar streaming technologies.
Experience with Linux, containerization, CI/CD pipelines, and Infrastructure-as-Code.
Graph analytics frameworks and algorithms, including graph traversal, centrality, community detection, similarity analysis, and link prediction.
Experience with Keycloak, and security best practices (authN/Z, secrets management).
Experience building and maintaining microservices in Kubernetes.
Familiar with infrastructure-as-code (CloudFormation, Terraform, Pulumi).

NMECDTP-ALL

#ASBAIf you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

July 27, 2026For U.S.

Positions:

While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range $131,300.00 - $237,350.00The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

Leidos is an industry and technology leader serving government and commercial customers with smarter, more efficient digital and mission innovations. Headquartered in Reston, Virginia, with 47,000 global employees, Leidos reported annual revenues of approximately $16.7 billion for the fiscal year ended January 3, 2025. For more information, visit Leidos .Pay and benefits are fundamental to any career decision. That's why we craft compensation packages that reflect the importance of the work we do for our customers. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available at leidospay-benefits .Beware of fake employment opportunities using Leidos' name. Leidos will never ask you to provide payment-related information during any part of the employment application process (i.e., ask you for money), nor will Leidos ever advance money as part of the hiring process (i.e., send you a check or money order before doing any work). Further, Leidos will only communicate with you through emails that are generated by the Leidos automated system - never from free commercial services (e.g., Gmail, Yahoo, Hotmail) or via WhatsApp, Telegram, etc. If you received an email purporting to be from Leidos that asks for payment-related information or any other personal information (e.g., about you or your previous employer), and you are concerned about its legitimacy, please make us aware immediately by emailing us at LeidosCareersFraudleidos .If you believe you are the victim of a scam, contact your local law enforcement and report the incident to the U.S. Federal Trade Commission .All qualified... 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Senior Data Engineer