Data Engineer (Robotics) (all genders) - Verification & Validation

Data Engineer (Robotics) (m/f/d) – Verification & Validation

Join us as a Data Engineer – Robotics in our Verification & Validation team and help shape the future of autonomous mobility!

As the Verification & Validation team, we ensure that autonomous driving systems are safe, reliable, and ready for the road. Our mission is to answer the critical question: “Is the system ready to deploy?”

We build and maintain the data foundations that power simulation, testing, and real‑world validation—enabling engineers across the company to trust the data they work with.

What you will do

Build robust data pipelines

• Design, build, and maintain high‑performance data pipelines that ingest, synchronize, transform, and validate sensor data from simulation and real‑world test fleets.
• Work with robotics logging formats (MCAP, ROSbags, or similar): reading, writing, parsing, indexing, validating, and transforming log data at scale.
• Process multi‑modal sensor data including camera, LiDAR, radar, GPS, and vehicle bus data.
• Handle timestamp synchronization, sensor alignment, and high‑frequency data processing.
• Build cloud‑scale storage solutions and data architectures for large datasets.

Ensure data quality

• Compare simulation data against real‑world logs, ensuring consistency and evaluating data quality.
• Detect anomalies, assess data robustness, and ensure dataset quality for machine learning, perception, and downstream teams.
• Perform data preparation, metadata extraction, indexing, and quality assessment.
• Interpret complex sensor logs, identify issues, and extract actionable insights.
• Debug data issues across multiple sensors and sources.

Collaborate across teams

• Work closely with Simulation, Perception, ML, and Systems teams to translate requirements into robust data solutions.
• Support cross‑functional teams with data‑driven insights for test strategy optimization.
• Share knowledge through documentation, presentations, and collaboration sessions.
• Contribute to continuous improvement of data processes and methodologies.

What will help you to fulfill your role

• Background in data engineering, robotics, scientific computing, simulation, or a related technical field—with hands‑on experience building data pipelines for sensor‑rich or high‑throughput environments.
• Strong programming skills in Python and/or C++, plus proficiency with Bash and Linux environments.
• Experience with time‑series logging formats used in robotics or simulation (such as MCAP, ROSbags, HDF5, or similar) and have built large‑scale data pipelines for complex datasets.
• Experience with multi‑modal sensor data or high‑dimensional time‑series data. Experience with camera, LiDAR, radar, or similar sensor types is valuable—but equivalent experience from scientific instrumentation, gaming, or simulation is equally relevant.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and understand how to build scalable data architectures.
• Strong debugging skills and enjoy investigating complex data issues across multiple sources.
• Curious and analytical, with persistence when untangling intricate datasets. You don’t just find problems—you understand root causes and build solutions that prevent them.

Nice to have

• Experience with ROS / ROS2 or other robotics middleware.
• Background in simulation platforms (Unity, Unreal, CARLA, Gazebo, or similar).
• Contributions to open‑source robotics or data tooling.
• Experience with SLAM, mapping, localization, or perception systems.
• Familiarity with visualization tools such as Foxglove, RViz, or custom interfaces.
• Experience with workflow orchestration (Airflow, Kubeflow, Prefect).
• Experience with containerised environments (Docker, Kubernetes).
• Understanding of safety standards (ISO 26262, SOTIF) or automotive regulations.
• Knowledge of sensor fusion, calibration, or coordinate systems.
• Comfortable working in a multi‑national team with occasional travel for meetings (e.g., PI Planning, ~1x/month). You value diverse perspectives and enjoy working in a hybrid environment where experimentation and learning are encouraged.
• Most importantly, excitement about building the data foundations that power safe autonomous driving.

Benefits in a nutshell

• Competitive salary (including bonus)
• Hybrid work setup: Work from home or one of our offices - you and your team decide how often to meet, blending flexibility with collaboration!
• Flexible working hours and the possibility of flexible work arrangements depending on your needs (parenting, care work, volunteering, etc.)
• Budget and monthly expense allowance for home office setup
• Possibility of remote work from outside Germany for up to 6 weeks per year from over 35 countries - learn more in our blog!
• Public transport ticket (fully subsidised “Deutschlandticket”) for commuting and travelling throughout Germany and discount on MOIA rides
• Subsidised fitness club membership or bike leasing
• Learning environment with continuous learning days, job rotation, trainings and workshops, coaching, conferences, books, and language classes
• Mental health support, 1:1 sessions with external professionals and mental unload workshops
• 30 vacation days, sabbatical and unpaid leave option
• Relocation support with service provider (visa, administration, etc.)
• Dog‑friendly offices

Diversity & Inclusion

We are a member of Charta der Vielfalt and are dedicated to actively fostering a workplace that celebrates and promotes diversity in various aspects such as age, gender identity, race, sexual orientation, physical or cognitive ability, and ethnicity. At MOIA, we embrace a culture where people are accepted, respected, valued, appreciated, and included.

In our commitment to promoting diversity and inclusivity, we regularly provide unconscious bias training to all our employees. Furthermore, we continuously strive to enhance our hiring process by ensuring a diverse hiring panel.

How to apply

We value authenticity and personal insights in your application responses. While AI tools can be useful, we encourage you to answer the following questions based on your own experiences and understanding. This helps us keep a human touch and better evaluate your unique perspective and match for the role.

Please do not include your picture, age, address, or any other details unrelated to your qualifications and suitability for the role. Additionally, we anonymise applications during the initial review phase by removing personally identifiable information. This ensures that our evaluation focuses solely on your skills, experience, and potential – supporting a fair and inclusive hiring experience for all candidates.