Data Engineer, Data Quality & Provenance

Requirements

• Strong hands-on Python and SQL skills, with solid production software-engineering fundamentals
• Experience designing and operating large-scale distributed data systems
• Hands-on experience with distributed processing and workflow orchestration technologies
• Experience building and operating cloud-based data platforms
• Proven ownership of data quality, lineage, observability, reproducibility
• Experience translating ambiguous requirements into durable, reusable platform capabilities

Nice to Haves

• Experience in autonomous vehicles, robotics, or another sensor-rich domain
• Familiarity with time-synchronised sensor data or geospatial data
• Understanding of ML training, evaluation, simulation workflows

What You'll Be Doing

• Design, build and operate scalable batch and streaming pipelines for multimodal fleet and simulation data
• Create data models, catalogs, indexes and query capabilities for sensor, vehicle-state, map and event data
• Build versioned, reproducible datasets for training, evaluation, replay, scenario mining, and safety analysis
• Develop robust workflows for data ingestion, transformation, curation, labeling, and data-quality validation
• Establish standards for lineage, observability, access controls, and cost management
• Improve the performance, reliability, and economics of large-scale storage and compute workloads

Perks and Benefits

• Full-time role based in Leonburg, Germany
• Hybrid working policy combining office and remote work
• Inclusive interview experience with accommodations available
• Commitment to diversity, fair culture, and respect for all employees