Data Engineer, Data Quality & Provenance

Before the detail, here's the challenge you'd help us solve.We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that.Here’s what this particular role covers.🛠️ About our Data Quality & Provenance Team Our Data Quality & Provenance team sits within Wayve’s AI Platform organisation and builds the trusted data foundations behind our self-driving technology. We transform vast volumes of fleet and simulation data into discoverable, reliable and reproducible datasets for model training, evaluation, replay, scenario mining and safety analysis. Operating at petabyte scale, the team defines the data products, standards and systems that enable our engineering teams to use data with confidence. 🧠 Your day-to-day Design and operate scalable batch and streaming pipelines for multimodal fleet and simulation data.Build data models, catalogues, indexes and query capabilities that make sensor, vehicle-state, map and event data easy to discover and use.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. 🧩 What you’ll be working onPetabyte-scale data products supporting autonomous-driving development across ML, autonomy, simulation and safety teams.Trusted datasets with strong versioning, lineage and reproducibility guarantees.Metadata, geospatial and temporal indexing that enables data discovery, selection and scenario mining.Systems that combine real-world fleet logs with simulation and synthetic data for closed-loop development.Data-quality