Principal Data Engineer, Data Quality & Datasets Pipelines

Wayve • Sunnyvale, CA

1d • $290,000 - $340,000 • Hybrid

About The Position

Wayve’s Datasets team owns the driving data that its AI Driver learns from, including ingestion, annotation, retrieval, and data quality. The team manages data that is growing from hundreds of petabytes toward exabyte scale and determines what data to keep and where, building systems to put those decisions into practice.

The Principal Data Engineer will turn dataset strategy into practical systems for moving, filtering, retaining, and offloading driving data. The role focuses on the engineering around pre-ingestion selection models: how data moves, where models run, and how offload policies work. It also involves making early, low-compute decisions that avoid costly standardisation and enrichment of low-value data, while preserving useful behavioural and environmental coverage for model training.

The engineer will work closely with the dataset strategy lead and data infrastructure and storage teams, shipping and iterating on solutions for data quality and storage-cost reduction. Wayve operates a hybrid working model, combining office collaboration with remote work. The role may include hands-on work in vehicle workshops and labs.

Requirements

• Experience as a senior data or software engineer running data ingestion or data quality pipelines at petabyte scale.
• Strong Python and Spark skills.
• Cloud data engineering experience.
• Good judgment about data filtering and quality, including how to verify valuable data has not been discarded.
• Ability to ship practical solutions quickly and iterate on live systems.
• Software engineering orientation, building systems around models rather than building the models themselves.
• Enjoys working closely with data infrastructure and storage teams.

Nice To Haves

• Experience in autonomous vehicles, robotics, fleet data, or high-volume IoT.
• Experience with retention, offload, and data lifecycle policies.

Responsibilities

• Implement and iterate filtering, retention, and offload policies across hot, cold, archive, and delete storage.
• Build data movement and pipelines used by the pre-ingestion selection model.
• Determine where and how selection models run, balancing compute cost against data value.
• Build early, low-compute decision points to avoid expensive standardisation and enrichment of low-value data.
• Work with storage and data infrastructure teams and monitor data quality to ensure datasets reflect model-training needs.
• Move, filter, retain, and offload driving data at hundreds-of-petabytes scale.
• Deliver measurable storage-cost savings through early, low-compute decisions.
• Ensure datasets provide useful behavioural and environmental coverage for training.
• Partner with the dataset strategy lead and data infrastructure team to ship practical solutions quickly.

Benefits

• Salaries benchmarked against the market annually.
• Meaningful equity.
• Relocation support and visa sponsorship where applicable.
• Hybrid working and core hours.
• Opportunity to work hands-on in vehicle workshops and labs.
• Learning and development budgets, with support for training, conferences, and growth.
• Comprehensive benefits including health insurance, dental insurance, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, and wellbeing partner discounts.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed