Full-Stack Geospatial Data Engineer

About the role

This fully remote position offers the chance to build cutting‑edge geospatial and climate intelligence solutions. You will transform massive Earth observation datasets into actionable insights for sustainability, environmental monitoring, and climate finance customers.

Key responsibilities

• Design and implement end‑to‑end geospatial data pipelines, including satellite imagery ingestion, processing, storage, and API services.
• Develop scalable backend services and geospatial APIs that deliver environmental intelligence.
• Create intuitive frontend applications and dashboards for data visualization using modern web technologies.
• Optimize large‑scale data workflows for performance, reliability, and cost efficiency.
• Implement infrastructure automation, CI/CD pipelines, monitoring, and cloud‑native operational practices.
• Collaborate with researchers, scientists, and stakeholders to translate complex requirements into production systems.
• Lead engineering best practices through code reviews, architectural guidance, and mentorship.
• Contribute to hiring and help define the long‑term technical vision of the platform.

Required profile

• Strong full‑stack engineering experience with Python, TypeScript, React, Next.js, and Node.js.
• Proven ability to build and maintain large‑scale data pipelines and distributed processing systems.
• Hands‑on experience with cloud storage, object stores, data orchestration platforms, and modern data formats.
• Deep knowledge of geospatial technologies, GIS tools, remote sensing workflows, and satellite imagery processing.
• Experience with cloud infrastructure, containerization, Infrastructure as Code, observability tools, and DevOps practices.
• Solid understanding of distributed systems, data versioning, scalability, and reliability.
• Self‑starter who can work independently in a fast‑moving environment.

Required skills

• Python
• TypeScript
• React
• Next.js
• Node.js
• API development
• Large‑scale data pipelines
• Distributed data processing
• Cloud storage architectures
• Object stores
• Data orchestration platforms
• Modern data formats
• Geospatial technologies
• GIS tools
• Remote sensing workflows
• Satellite imagery processing
• Cloud infrastructure
• Containerization
• Infrastructure as Code (IaC)
• Observability tools
• DevOps practices
• Distributed systems concepts
• Data versioning
• Scalability
• System reliability