Role Overview
- Build the data services and infrastructure that power our geospatial intelligence platform.
- Design and implement scalable backend services using TypeScript
- Build systems for ingesting, storing, and serving large geospatial datasets
- Develop data pipelines and APIs that deliver machine learning results and geospatial data to the platform
- Work with high-throughput NoSQL databases such as Cassandra or Scylla
- Design data architectures capable of handling petabyte-scale satellite datasets
- Optimize backend systems for large-scale spatial queries and time-series data
- Collaborate closely with ML engineers, frontend developers, and geospatial analysts
- Own backend features end-to-end, from system design to production deployment
- Contribute to architectural decisions as we scale our platform and data infrastructure
Technical Challenges
The backend systems you will work on operate at the intersection of AI, enterprise software systems, and distributed data infrastructure.
Key challenges include:
- Processing millions of geodata points
- Building high-performance enterprise software solutions
- Designing scalable architectures for time-series environmental data
- Integrating machine processes into production systems
- Optimizing storage and retrieval for large spatial datasets
This role is ideal for engineers who enjoy building data-heavy systems, working with distributed databases, and solving problems around scale, performance, and data architecture.
Requirements
- Strong backend development experience using TypeScript
- Experience building data-intensive backend services
- Experience working with distributed or NoSQL databases such as Apache Cassandra or Scylla
- Solid understanding of scalable system design and data architecture
- Experience designing APIs and backend services for large-scale applications
- A strong product mindset and ability to think beyond implementation
- Experience working in agile teams
Language requirements:
- English (C1 and above)
- German (B1 and above)
Nice to have:
- Experience with Java-based backend systems
- Experience working with geospatial or environmental data
- Experience with data pipelines or machine learning systems
- Experience operating systems handling large-scale datasets
Prior experience with remote sensing or satellite data is not required — you will work closely with our ML and geospatial teams and learn these domains on the job.
Tech Stack
- Apache
- Cassandra
- Java
- NoSQL
- Remote Sensing
- TypeScript
Benefits
- Work on technology helping companies protect forests and ecosystems
- Build systems combining AI, satellite data, and geospatial intelligence
- Solve engineering challenges involving massive datasets and distributed data infrastructure
- Collaborate with a multidisciplinary team of engineers, ML specialists, and geospatial analysts
- Join a fast-moving team with strong ownership and short decision paths
- Work from our Munich office near Sendlinger Tor with around 40 colleagues
- Regular demo lunches and knowledge-sharing sessions
- Hybrid work setup with strong in-person collaboration