Full-Stack Geospatial Data Engineer

Accountabilities:

• Design and build end-to-end geospatial data systems, including satellite imagery ingestion, processing pipelines, storage architecture, and API services.


• Develop and maintain scalable backend services and geospatial APIs that deliver environmental intelligence to customers and stakeholders.


• Create intuitive frontend applications and dashboards using modern web technologies to support data visualization and decision-making.


• Optimize large-scale data workflows handling massive volumes of Earth observation data while ensuring performance, reliability, and cost efficiency.


• Implement infrastructure automation, CI/CD pipelines, monitoring solutions, and cloud-native operational practices.


• Collaborate with researchers, scientists, and technical stakeholders to translate complex geospatial requirements into production-ready systems.


• Lead engineering best practices through code reviews, architectural guidance, and technical mentorship.


• Contribute to hiring efforts and help establish the long-term technical vision for the platform.

Requirements

• Strong full-stack engineering experience with Python, TypeScript, React, Next.js, Node.js, and modern API development frameworks.


• Expertise in building and maintaining large-scale data pipelines and distributed data processing systems.


• Hands-on experience with cloud storage architectures, object stores, data orchestration platforms, and modern data formats.


• Deep knowledge of geospatial technologies, remote sensing workflows, GIS tools, and satellite imagery processing.


• Experience with cloud infrastructure, containerization, Infrastructure as Code, observability tools, and DevOps practices.


• Strong understanding of distributed systems concepts, data versioning, scalability, and system reliability.


• Ability to work independently in fast-moving environments with evolving requirements and minimal supervision.


• Excellent problem-solving, communication, and collaboration skills.


• Passion for climate technology, environmental sustainability, and mission-driven innovation.


• Experience leading engineering initiatives, machine learning systems, GPU-accelerated processing, or environmental science projects is considered a strong advantage.

• Competitive salary ranging from $40,000 to $110,000 annually for U.S.-based candidates, depending on experience and location.


• Flexible remote-first work environment with asynchronous collaboration practices.


• Hardware, conference, and professional learning stipend.


• Opportunity to work alongside leading academics, researchers, and industry experts.


• Significant ownership over product architecture and technical decision-making.


• Career growth opportunities including technical leadership and mentoring responsibilities.


• Exposure to cutting-edge geospatial, climate intelligence, and environmental data technologies.


• Meaningful work contributing to climate action, sustainability initiatives, and environmental impact at global scale.

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