Data Engineer, Data Quality & Provenance

Wayvemid

En corto

→Construyes pipelines y datasets confiables a escala petabyte para vehículos autónomos.
→Trabajas con datos multimodales de flota y simulación, asegurando calidad, trazabilidad y reproducibilidad.
→Destaca por definir estándares de datos en un entorno en rápido crecimiento, con alto impacto en la inteligencia artificial embadada.

No se requiere inglés explícitamente, pero el puesto es en inglés (el texto está en inglés

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¿Qué piden?

✓Excelentes habilidades en Python y SQL con fundamentos de ingeniería de software.
✓Experiencia en sistemas distribuidos de datos a gran escala, más allá de pipelines pequeños.
✓Manejo de herramientas como Spark, Flyte, Airflow o equivalentes para orquestación de workflows.
✓Experiencia operativa en plataformas de datos en la nube con almacenamiento objeto.
✓Capacidad comprobada para gestionar calidad, trazabilidad y respuestas a incidentes en datos de producción.
✓Capacidad para traducir requisitos ambiguos en soluciones reutilizables y duraderas.

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PythonSQLSparkFlyteAirflowCloud-based data platformsObject storageData versioningData catalogsTime-synchronized sensor data

¿A quién escribirle en Wayve?

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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 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

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