R3 Robotics is developing the AI-powered dismantling platform that transforms end-of-life electric vehicle systems into strategic sources of critical materials. As global electrification accelerates, the surge in batteries and e-motors requires automated solutions that manual disassembly cannot provide. We are addressing this industrial bottleneck by enabling the automated dismantling of complex systems at scale through computer vision, artificial intelligence, and specialized robotic tooling.
Following a successful €20M Series A funding round led by HG Ventures and Suma Capital, we are expanding across Europe and preparing for our entry into the United States market in 2026. We partner with major industrial recyclers and automotive OEMs to deliver measurable impact. If you seek to work on advanced robotics within a well-funded organization scaling internationally, this is your opportunity.
Your Role
At R3 Robotics, data is the fuel for our machines. Our extensive curated datasets on battery packs help train smarter algorithms and make our robots more flexible. Our robots in turn are continuously sensing, learning, and gathering more data which flows into our data lake for consumption by various applications.
As a Data Engineer, your role is to ensure reliable execution of our data flows and lead data solution design in support of various hardware and software consumers.
Your Responsibilities
- Maintain, extend, and lead the evolution of our data lake architecture
- Create data pipelines that ingest granular, near real time machine telemetry and publish them to the data lake
- Create and update queries based on machine data to provide insights on performance and other metrics
- Maintain clean data sets with data quality controls for consumption by business teams
- Own and administer our cloud platforms and accounts which host data and data-intensive applications
- Work with software engineers to ensure appropriate instrumentation of the system so all data outflows are captured
- Set up alerts and mechanisms to proactively identify data issues or metrics deviations