Data Engineer, Data Quality & Provenance

As a Data Engineer focused on Data Quality & Provenance, you will build the data foundation that enables Wayve’s autonomous-driving development. You’ll turn vast volumes of fleet and simulation data into trusted, discoverable and reproducible datasets that ML, autonomy, simulation and safety teams can use with confidence. This is a high-impact opportunity to define the data products, standards and operating model behind embodied intelligence at petabyte scale.

Key responsibilities:

• Design, build and operate scalable batch and streaming pipelines for multimodal fleet and simulation data.
• Create data models, catalogs, indexes and query capabilities that make sensor, vehicle-state, map and event data easy to discover and use.
• Build versioned, reproducible datasets for training, evaluation, replay, scenario mining and safety analysis.
• Develop robust workflows for data ingestion, synchronisation, transformation, curation, labelling and data-quality validation.
• Partner with autonomy, ML, simulation and safety engineers to define schemas, APIs and data contracts.
• Establish strong standards for lineage, observability, access controls, retention and cost management across the data platform.
• Improve the performance, reliability and unit economics of large-scale storage and compute workloads.

In order to set you up for success as a Data Engineer, Data Quality & Provenance at Wayve, we’re looking for the following skills and experience.

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