Geospatial Cloud Engineer (TS/SCI) – Real-Time Pipelines

aqua IT; Herndon (VA); On-site; USD 120,000 - 180,000; Full time

Job description

* THIS JOB REQUIRES AN ACTIVE TS/SCI CLEARANCE *

We are seeking several Software Engineers to support the development of scalable geospatial data processing and cloud-native systems supporting DoD and Intelligence Community programs. This role will involve designing and maintaining distributed data pipelines, geospatial processing workflows, streaming architectures, and cloud infrastructure supporting near real-time analytics and large-scale geospatial data environments.

Candidates may support a mix of backend software engineering, geospatial data engineering, cloud infrastructure, streaming/data pipeline development, spatial database engineering, and geospatial algorithm development depending on team placement and technical strengths. Work will include development in AWS cloud-native environments using Python and Infrastructure-as-Code practices, while supporting highly scalable distributed systems and production-grade geospatial solutions.

Responsibilities:

• Design, develop, and maintain scalable cloud-native software systems and data pipelines
• Support real-time data ingestion, processing, transformation, and analytics workflows
• Build and optimize geospatial processing solutions, spatial algorithms, and vector data workflows
• Develop and maintain distributed systems leveraging AWS services and streaming architectures such as Apache Kafka
• Design and optimize database solutions including PostgreSQL/PostGIS and cloud-native data services
• Implement Infrastructure-as-Code (IaC) solutions using AWS CDK and modern deployment strategies
• Support ETL/ELT workflows, API integrations, performance optimization, and operational monitoring
• Collaborate across engineering teams to troubleshoot production issues and improve system scalability and reliability

Required Qualifications:

• Active TS/SCI Clearance
• 5+ years of software engineering experience in cloud-first or distributed environments
• Experience with AWS cloud-native services and Infrastructure-as-Code concepts
• Familiarity with cloud services such as Lambda, API Gateway, S3, RDS, DynamoDB, SQS, SNS, or EventBridge
• Experience with containerization technologies such as Docker, ECS, EKS, or Kubernetes
• Strong understanding of scalable system design, performance optimization, and troubleshooting

Desired Experience:

• Apache Kafka or real-time streaming architectures
• Geospatial data processing, spatial algorithms, or vector data workflows
• ETL/ELT pipelines, analytics platforms, or data lake architectures
• AWS CDK and multi-environment deployment strategies
• Cloud-native geospatial application development and large-scale distributed processing environments