Data Engineer, Data Quality & Provenance

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 Wayve, we’re looking for the following skills and experience.

Essential

• Strong hands-on Python and SQL skills, with solid production software-engineering fundamentals.
• Experience designing and operating large-scale distributed data systems, beyond small-scale analytics or reporting pipelines.
• Hands-on experience with distributed processing and workflow orchestration technologies, such as Spark, Flyte, Airflow or equivalent tools.
• Experience building and operating cloud-based data platforms using object storage, including data organisation, versioning, querying, governance and cost management.
• Proven ownership of data quality, lineage, observability, reproducibility and incident response for production data workflows.
• Experience translating ambiguous requirements from ML, data-science, robotics or similarly technical teams into durable, reusable platform capabilities.
• Comfort operating in ambiguity and helping define the boundaries, standards and ways of working for a growing data platform.

Desirable

• Experience in autonomous vehicles, ADAS, robotics, mapping, drones or another sensor-rich domain.
• Familiarity with time-synchronised sensor data, geospatial data, or multimodal datasets.
• Understanding of ML training, evaluation, simulation or closed-loop development workflows.

This is a full-time role based in our office in Leonburg, Germany.  At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.