SWE, Data Ingestion

You are an experienced Data Engineer, Platform Engineer or Distributed Systems Engineer who enjoys working on large-scale production data systems.

You have seen how data pipelines behave in the real world: messy inputs, strange edge cases, corrupt files, stalled queues, unexpected formats and failures that only appear at scale.

You are comfortable digging into those problems, finding the root cause and making systems better as a result.

You combine strong technical depth with a practical, collaborative approach.

You can take ownership of complex systems, work effectively across teams and balance urgent operational needs with thoughtful, durable engineering improvements.

• Strong production experience with Apache Spark.
• Strong Python engineering experience.
• Experience building, debugging or operating large-scale data-ingestion, ETL or data-processing pipelines.
• Experience with distributed data-processing systems.
• Ability to optimise jobs for throughput, compute efficiency and reliability.
• Experience debugging production pipeline failures.
• Comfort working with messy, corrupt, incomplete or inconsistent data.
• Understanding of orchestration across multi-step pipelines and downstream dependencies.
• Ability to work independently in a fast-moving, highly technical environment.
• A practical, delivery-focused mindset with a focus on continuous improvement.
• Experience working at significant data scale, ideally PB-scale or similarly high-throughput environments.

Experience in one or more of the following areas would be a strong advantage:

• Airflow, Flyte, Databricks Workflows or similar orchestration tooling.
• Databricks, Delta Lake or Delta tables.
• Scala or Java, especially in Spark-based environments.
• Queue-based processing, retry handling and priority data workflows.
• High-throughput batch data-processing systems.
• Production systems with many data producers, consumers or external data sources.
• Handling third-party, partner or supplier data with inconsistent formats and quality issues.
• Automotive, robotics, autonomy, mapping, ML data platforms or embodied AI environments.
• Cost optimisation for compute- and storage-heavy data platforms.
• High-performance engineering experience from domains such as trading, where it includes relevant distributed-systems or throughput-focused work.

This is a full-time, permanent role based in our Sunnyvale, CA office. and the reasonably estimated salary for this role ranges from $210,000 to $250,000, plus a competitive equity package.

Actual compensation is based on the candidate's skills, qualifications, and experience.

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, with time spent working from home.

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

For more information visit Careers at Wayve.

To learn more about what drives us, visit Values at Wayve

DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews.

However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.