Data Engineer, Data Quality & Provenance

Job description

About us Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact. Make Wayve the experience that defines your career! The role 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. About you In order to set you up for success as a Data Engineer, Data Quality & Provenance at W…