Satellite Data Processing Engineer

Posted: 2026-09-24

Welcome to Planet. We believe in using space to help life on Earth.

Planet designs, builds, and operates the largest constellation of imaging satellites in history. This constellation delivers an unprecedented dataset of empirical information via a revolutionary cloud-based platform to authoritative figures in commercial, environmental, and humanitarian sectors. We are both a space company and data company all rolled into one.

Customers and users across the globe use Planet's data to develop new technologies, drive revenue, power research, and solve our world’s toughest obstacles.

As we control every component of hardware design, manufacturing, data processing, and software engineering, our office is a truly inspiring mix of experts from a variety of domains.

We have a people-centric approach toward culture and community and we strive to iterate in a way that puts our team members first and prepares our company for growth. Join Planet and be a part of our mission to change the way people see the world.

Planet is a global company with employees working remotely world wide and joining us from offices in San Francisco, Washington DC, Germany, Austria, Slovenia, and The Netherlands.

Image Quality Support (IQS) makes sure Planet's imagery meets that bar. We sit between imaging operations, satellite operations, software engineering, and the business — close enough to engineering to build our own tools, close enough to customers to know what "quality" means to them.

We're looking for a Satellite Data Processing Engineer to help assess and automate imagery quality across Planet's satellite fleet. You'll split your time between hands-on visual QA and writing the software that scales it — a hybrid of remote-sensing know-how and software engineering, building up both with guidance from senior teammates.

This is a full-time, hybrid role which will require you to work from our Berlin office 3 days per week.

Impact You’ll Own

- Assess satellite imagery, manually and via automated tooling, against contractual and technical quality standards.

- Help build and maintain the internal tools that power quality assessment — from QGIS-based QA tooling to backend scripts and data pipelines.

- Support investigations into customer-reported quality disputes, gathering technical evidence for the team's decisions.