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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Scientific Data Engineering Specialist - **Company:** Booz Allen Hamilton Inc. - **Location:** Fairfax, VA, United States - **Salary:** $77,600.0 - $176,000.0 - **Contract:** Permanent contract - **Skills:** Kubernetes Security, Java (Programming Language), Geographic Information Systems, Spring Security, Application Programming Interfaces (APIs), Amazon Elastic Compute Cloud, Amazon S3, Apache HTTP Server, ArcGIS (Software), Cloud Engineering, Information Engineering, Data Systems, DevOps, Electronic Data Interchange (EDI), Hibernate (Java), Identity and Access Management, Java Persistence API, Junit, PostgreSQL, MongoDB, Operational Data Store, OpenShift, PostGIS, Redis, Mockito, Amazon Simple Notification Service (SNS), SonarQube, Data Streaming, Systems Architecture, Data Logging, Performance Testing, Test-Driven Development (TDD), Data Ingestion, Spring Cloud, Amazon ElastiCache, Spring-boot, Change Data Capture, Event Driven Architecture, Gitlab-ci, Integration Tests, Debezium, Kubernetes, Rancher, Apache Kafka, Decoding, Amazon Simple Queue Service (SQS), Terraform, Data Pipelines, Docker, Jenkins, Microservices - **Published:** October 21, 2026 - **Apply:** https://www.dice.com/job-detail/a5b74a4b-e50c-4ac3-8d52-68c27646156f ## About the Role * Experience with geospatial data processing using PostgreSQL, PostGIS, spatial queries, coordinate reference systems, spatial envelopes, and georeferenced data * Experience processing scientific data formats such as GOES-R, NEXRAD, GRIB2, SYNOPTIC, or polar-orbiter * Experience designing and implementing Java- and Spring-based microservices using technologies such as Spring Boot, Spring Cloud Gateway, Spring Security, WebFlux, JPA, and Hibernate * Experience building end-to-end scientific data workflows, including ingestion, decoding, transformation, georeferencing, storage, cataloging, and synchronized distribution across microservices * Experience developing scientific visualization capabilities, including real-time imagery access, interactive mapping, ArcGIS integrations, plotting, or meteorological visualizations * Experience engineering cloud-native scientific data systems supporting high-volume environmental, observational, weather, or geospatial data * Experience developing event-driven data pipelines using messaging and change-data-capture technologies such as Apache Pulsar, Kafka, and Debezium * Experience defining system architecture, developing technical strategies, and presenting technical direction to senior government or program stakeholders * Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements * Bachelor's degree Nice If You Have: * Experience modernizing legacy scientific or government systems into decoupled, cloud-native architectures * Experience with AWS services such as EKS, S3, SQS, SNS, IAM, EC2, and ElastiCache * Experience with Kubernetes, Docker, Helm, Jenkins, GitLab CI/CD, OpenShift, Rancher, or Terraform * Experience with scientific or operational data stores and caching technologies such as MongoDB, Redis, PostgreSQL, and PostGIS * Experience with Java virtual threads, structured concurrency, reactive systems, or other techniques for processing large numbers of concurrent files or requests * Experience with automated quality and security tooling such as JUnit, Mockito, Testcontainers, LocalStack, SonarQube, or container security scanning * Experience supporting meteorological, satellite, radar, atmospheric-science, or other environmental-data missions * Experience collaborating with government stakeholders, scientific users, engineering teams, DevOps teams, or quality-assurance organizations * Experience mentoring developers, supporting onboarding, or establishing shared engineering standards and reusable libraries ## Description Provide technical leadership in designing and implementing scalable data ingestion, storage, cataloging, API, and processing capabilities as a Scientific Data Engineering Specialist. Ensure that high-volume, secure, and reliable data pipelines operate effectively across various internal data teams. Contribute to modern cloud-based architectures and guide the development and optimization of microservices that support ingestion, transformation, and advanced processing workflows. Partner closely with engineering peers to evolve legacy data flows into event-driven systems and strengthen platform observability, metrics, and logging. Build and refine API and notification services to streamline data exchange and integration. Enhance metadata and catalog systems to improve data discoverability and synchronization with downstream users. Support strong quality practices, including test-driven development, integration testing, and performance validation. Participate actively in sprint activities, architectural discussions, and cross-team collaboration to help drive clarity, alignment, and technical direction. Work with us to use data for good. Due to the nature of work performed within this facility, U.S. citizenship is required.