Software Engineer - Geospatial Algorithms

Responsibilities:

• Demonstrated familiarity with software engineering practices specifically applied to geospatial data processing and the development of spatial algorithms at scale
• Strong understanding of vector geospatial data products and their associated processing pipelines, including ingestion, transformation, and quality validation workflows
• Thorough understanding of modern software engineering principles and cloud-native environments, with the ability to design and deploy scalable, production-grade geospatial solutions

Qualifications/Skills Required:

• TS/SCI with CI Poly required

• Must be willing to work in SCIF daily or as needed
• 5+ years of professional software engineering experience with cloud-first development approach
• 5+ years of hands-on experience with AWS CDK for Infrastructure as Code
• 3+ years building complex, reusable CDK constructs and stacks
• Proficiency in async programming and performance optimization* 3+ years implementing multi-environment deployment strategies using CDK
• 5+ years of advanced Python development experience
• 4+ years of data engineering experience
• ETL/ELT pipeline development using AWS services
• Experience with data lakes, data warehousing, and analytics platforms
• Real-time data processing and streaming architectures
• 3+ years with AWS cloud-native services
• Advanced knowledge of Lambda, API Gateway, EventBridge, SQS, SNS
• Experience with data services: RDS, DynamoDB, Redshift, S3, Athena
• Container orchestration with ECS, Fargate, or EKS
• Strong problem-solving abilities with proven track record of resolving complex technical challenges

Preferred Qualifications:

• 3+ years of software engineering experience with a focus on geospatial data processing and spatial algorithm development

• Hands-on experience working with vector geospatial data products and familiarity with common processing workflows, including ingestion, transformation, and quality validation
• Strong command of modern software engineering principles and cloud-native environments, with demonstrated ability to build and deploy scalable, production-grade geospatial solutions