Data Engineer, Data Quality & Provenance

About the role

The Data Quality & Provenance team builds the trusted data foundations for Wayve's self-driving technology. You will transform vast volumes of fleet and simulation data into discoverable, reliable, and reproducible datasets to support model training, evaluation, and safety analysis. This role involves designing scalable pipelines and defining the data systems that enable engineering teams to work with confidence.

Responsibilities

• Design and operate scalable batch and streaming pipelines for multimodal fleet and simulation data.
• Build data models, catalogues, indexes, and query capabilities for sensor, vehicle-state, and event data.
• Create versioned, reproducible datasets for training, evaluation, replay, scenario mining, and safety analysis.
• Develop workflows for data ingestion, synchronisation, transformation, curation, labelling, and quality validation.
• Partner with autonomy, ML, simulation, and safety engineers to define schemas, APIs, and data contracts.
• Improve the reliability, performance, and cost efficiency of large-scale storage and compute workloads.

Required skills

• Python
• SQL
• Distributed systems
• Spark
• Flyte
• Airflow
• Cloud data platforms
• Data governance

Nice to have

• Autonomous vehicles
• ADAS
• Robotics
• Geospatial data
• Multimodal datasets

Qualifications

• Solid production software-engineering fundamentals
• Production experience with distributed-processing and workflow-orchestration technologies

Benefits

• Health insurance
• Dental insurance
• Enhanced maternity and paternity leave
• Retirement or pension
• Learning and development budget
• Relocation support
• Visa sponsorship

About the Company

Wayve is building the leading AI platform for autonomous driving, pioneering an end-to-end AI approach that enables vehicles to learn directly from real-world experience. The company aims to make autonomy universal by developing a generalisable driving intelligence that can power any vehicle, anywhere.