Data Engineer Intern at Zoox in Foster City, CA

Summary: Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. As a Data Engineer Intern, you will build data pipelines and infrastructure to support autonomy development and analytics, while working closely with data scientists and engineers to enable efficient access to large datasets. Responsibilities: - Build data pipelines and infrastructure to support autonomy development - Develop ETL pipelines for processing vehicle logs - Create data platforms for metrics computation (using Databricks, Spark, Ray) - Build visualization dashboards (Looker, Grafana, Databricks) - Work on managing run metadata and pipeline processing - Enable data scientists and engineers to efficiently access and analyze petabytes of autonomous driving data - Build and maintain the pipelines that transform data at scale to support analytics throughout the company - Design and build data models for key business domains, such as autonomy, riders and fleet, simulation, etc - Define and execute on how high value key data assets are consumed to generate valuable insights by data scientists, engineers, and business users Required Qualifications: - Currently working towards a B.S., M.S., Ph.D., or advanced degree in a relevant engineering program - Must be returning to school to continue your education upon completing this internship - Good academic standing - Able to commit to a 12-week internship beginning in May or June of 2026 - At least one previous industry internship, co-op, or project completed in a relevant area - Ability to relocate to the Bay Area, California for the duration of the internship - Interns at Zoox may not use any proprietary information they are working on as part of their thesis, any published work with their university, or to be distributed to anyone outside of Zoox Preferred Qualifications: - Experience with big data technologies (Spark, Databricks, Airflow) - Knowledge of cloud platforms (AWS, GCP) and containerization (Docker, Kubernetes) - Familiarity with data warehousing and analytics platforms - Experience with streaming data processing - Understanding of ML infrastructure and feature stores - Knowledge of data quality, monitoring, and observability tools - Experience with autonomous vehicle data or sensor data processing - Experience with large scale streaming platforms (e.g. Kafka, Kinesis) and storage engines (e.g. HDFS, HBase) Required Skills: Spark, Databricks Important Skills: AWS, GCP, Docker, Kubernetes, Kafka, Kinesis Nice-to-Have Skills: Airflow, Data warehousing, Streaming data processing, ML infrastructure, Data quality tools, Autonomous vehicle data, HDFS, HBase Benefits: Medical insurance, A housing stipend (relocation assistance will be offered based on eligibility)