Data Engineer
R3 Robotics · Kuppenheim, Baden-Württemberg, Germany
Robotics Engineering · 11-50 employees
About the role
You will maintain and evolve the data lake architecture while creating robust pipelines to ingest machine telemetry. Additionally, you will collaborate with software engineers to ensure proper system instrumentation and provide actionable insights through data analysis.
What they look for
Requirements
The ideal candidate has 3+ years of experience in Python data engineering and advanced expertise in SQL and cloud platforms like AWS and Azure. You should also be proficient in managing document databases, containerized services, and modern data observability tools.
Benefits
Full description
Your mission
Join us in solving one of industrial robotics' toughest challenges. 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
Your profile
- Python data engineering (3+ years): Building production ETL/ELT pipelines and data services in Python, with sound engineering practice (Git, code review, testing, linting).
- Advanced SQL & databases: Expert PostgreSQL and analytical SQL, and strong data modeling for analytics.
- Cloud platforms (AWS & Azure): Hands-on with AWS (S3, Lambda, Glue, Athena/Presto) for data lake architectures, plus experience with Azure (e.g. Blob Storage) and secure credential/IAM management across environments.
- Pipelines & integrations: Event-driven and message-queue pipelines, incremental sync patterns, and REST API connectors to SaaS systems (e.g. HubSpot, ClickUp).
- MongoDB: Modeling and querying document data, operating Atlas across environments, and running safe data migrations.
- Airtable / low-code platforms: Building and maintaining Airtable solutions and migrating them to more robust databases as data scales.
- Data quality & reliability: Data validation and consistency checks across systems, and backfills and cleanup of production data.
- BI & reporting: Building dashboards (Metabase preferred; Streamlit, Superset, Power BI, or Tableau acceptable)
- DevOps & administration: Docker and Linux for containerized services, plus GitHub Enterprise administration and access governance.
- AI tooling: Fluent with AI developer tools (e.g. Claude, GitHub Copilot) as a natural part of the development workflow, moving faster while applying sound judgment on the output.
- Monitoring & observability: Setting up metrics and alerting with Prometheus, Grafana, and node exporter, plus CloudWatch alarms for cloud workloads.
Why us?
- High degree of collaboration and autonomy while working with a group of highly skilled, committed and supportive peers
- Transparent culture where everyone is highly valued
- Development of your professional skills and knowledge by taking ownership of challenging tasks and responsibilities, supported by leads and peers
- “Getting things done” attitude, and access to cutting edge technologies
- Complementary Health Insurance
About us
AUTOMATED DISMANTLING.
