Data Engineer, Data Quality & Provenance

Meyandy LLC; Northern (KY); Hybrid; USD 110,000 - 170,000; Full time

Job summary

Wayve is seeking a Data Engineer focused on Data Quality & Provenance to build the data foundation for autonomous-driving development. You will turn fleet and simulation data into trusted datasets for ML, autonomy, simulation and safety teams to use with confidence.

You will own data quality, lineage, observability, and reproducibility for production data workflows, collaborating with ML, autonomy and safety engineers to define schemas, APIs and data contracts at petabyte scale.

Qualifications

• Strong Python and SQL with production software engineering fundamentals.
• Experience designing and operating large-scale distributed data systems.
• Hands-on experience with distributed processing and workflow orchestration technologies (Spark, Flyte, Airflow).
• Experience building and operating cloud-based data platforms using object storage, governance and cost management.
• Proven ownership of data quality, lineage, observability, reproducibility and incident response for production data workflows.
• Ability to translate ambiguous requirements from ML, data-science, robotics or similar teams into reusable platform capabilities.
• Comfort operating in ambiguity and helping define boundaries and standards for a growing data platform.

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.

Skills

Python

SQL

Distributed data systems

Spark

Airflow

Tools

Flyte

Spark

Cloud storage & data catalogs

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 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, g… Data Engineer, Data Quality & Provenance — Wayve.