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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Geospatial Engineer - Cloud & DevOps - **Company:** Dewberry Engineers Inc. - **Location:** Fairfax, VA, United States (Remote available) - **Experience:** Experienced - **Salary:** $116,000 - $156,000 - **Contract:** Permanent contract - **Skills:** Geographic Information Systems, Application Programming Interfaces (APIs), Amazon Web Services, Amazon S3, Component-Based Software Engineering, Automation of Tests, Microsoft Azure, Cloud Computing, Cloud Engineering, Cloud Storage, Software Quality, Collaborative Software, Databases, Continuous Integration, Information Engineering, Database Design, DevOps, Distributed Systems, Spatial Databases, GIS Applications, Identity and Access Management, Python (Programming Language), Key Management, PostgreSQL, Open Source Technology, PostGIS, Quantum GIS (QGIS), Role-Based Access Control, Software Engineering, Software Vulnerability Management, Parquet, Data Logging, Data Processing, AWS Lambda, Git, Cloudformation, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Geospatial Data Abstraction Library (GDAL), AWS Fargate, Data Management, Restful APIs, Terraform, Software Version Control, Data Pipelines, Raster Graphics, Serverless Computing, Docker, Vulnerability Analysis - **Published:** November 14, 2026 - **Apply:** https://www.careerbuilder.com/job-details/geospatial-engineer-cloud-devops-fairfax-va--ae6e437b-3e21-4d53-ba18-0cb3f397b273 ## About the Role Software Engineering, Cloud Computing, DevOps, Risk, DevOps, Data Management, Software Engineering, Cloud Computing, Software Development, Workflow Analysis, * Bachelor's degree in Geography, Geographic Information Systems, Computer Science, Engineering, Data Science, Environmental Science, or a related field, or equivalent relevant experience. * Three or more years of relevant professional experience in geospatial development, data engineering, software development, cloud computing, or a related area. * Strong proficiency with Python for geospatial processing, automation, and data manipulation. * Experience with common geospatial technologies such as QGIS, GDAL, GeoPandas, Rasterio, PostGIS, or similar tools. * Experience working with geospatial raster and vector data and spatial databases. * Working experience with AWS and/or Azure cloud services. * Experience with Git and modern collaborative software-development practices. * Experience developing repeatable data-processing or analytical workflows. * Strong problem-solving skills and ability to work effectively with multidisciplinary technical teams. * Strong technical communication and documentation skills., * Experience with Docker and containerized geospatial processing. * Experience with Terraform, AWS Cloud Development Kit (CDK), AWS CloudFormation, or other infrastructure-as-code technologies. * Experience developing or maintaining CI/CD pipelines. * Experience with cloud storage, compute, and orchestration technologies such as Amazon S3, Amazon ECS or Fargate, AWS Batch, AWS Lambda, Azure Blob Storage, Azure Functions, or Kubernetes. * Experience with cloud-native geospatial formats and technologies such as Cloud Optimized GeoTIFF, GeoParquet or Parquet, Zarr, SpatioTemporal Asset Catalogs (STAC), or similar approaches. * Experience with PostgreSQL/PostGIS and geospatial database design and optimization. * Experience developing or consuming REST APIs or Open Geospatial Consortium APIs. * Experience with automated testing, logging, monitoring, and software quality practices. * Familiarity with security concepts including identity and access management, role-based access control, encryption, secrets management, and vulnerability scanning. * Experience with flood risk, water resources, environmental modeling, transportation, or other infrastructure-related geospatial applications. * Experience supporting FEMA, USACE, NOAA, USGS, state agencies, or similar public-sector clients. ## Description * Develop, automate, and maintain open-source geospatial data-processing and analytical workflows using Python and modern geospatial libraries and tools. * Design workflows for large raster, vector, and multidimensional geospatial datasets using both traditional GIS and cloud-native approaches. * Develop and maintain cloud-based geospatial processing environments using AWS and/or Azure. * Build reproducible deployment and processing workflows using Docker, infrastructure as code, continuous integration and continuous delivery (CI/CD), and version control. * Develop data pipelines that support ingestion, transformation, validation, analysis, cataloging, and delivery of geospatial information. * Develop and integrate geospatial databases, APIs, services, and application components. * Support scalable processing using containerized and parallel or distributed computing approaches. * Implement testing, logging, monitoring, documentation, and quality-control practices for production geospatial workflows. * Optimize cloud storage, compute, and data-access patterns for performance, reliability, and cost. * Apply appropriate security practices, including identity and access management, least-privilege access, secrets management, encryption, and vulnerability remediation. * Collaborate with engineers, scientists, data scientists, and software developers to translate analytical requirements into maintainable operational workflows. * Evaluate emerging geospatial and cloud technologies and help transition successful pilots into project and production environments. * Document architectures, workflows, code, and operational procedures and share knowledge across project teams.