Data Engineer, Fleet Data, Self-Driving

Help power the future of Full Self-Driving by unlocking the immense potential of data from millions of Tesla vehicles worldwide. On the Self-Driving Fleet Data team, you’ll work at the intersection of data engineering, analytics, and data science: building reliable pipelines and critical infrastructure for FSD model evaluation and improvements. This role owns critical data pipelines that feed landmark projects like the Full Self-Driving Vehicle Safety Report and surfaces the most valuable real-world scenarios from the fleet for training and evaluation. It builds the data foundation for setting priorities, measuring progress, and curating diverse datasets, work that has tangible impact on making scalable autonomy a reality.

Responsibilities

Design and maintain data platforms that make it easy for teams across the org to discover, query, and explore fleet data Design and implement data pipelines from ingestion to visualization to unlock the full potential of Tesla’s fleet data by sourcing, transforming, and serving new datasets Define and build metrics that measure Self-Driving performance and specific driving events, then turn them into insights that drive decisions Monitor and maintain infrastructure health with robust alerting, logging, and automation for scale and reliability Build automation, developer tools, internal libraries, and agentic tools that accelerate analysis and visualization across the company Manage inflow rate of fleet data to ensure consumers have a high volume of diverse data Iterate with AI engineering partners on effectiveness of new datasets Deliver world class, interactive visualizations and tooling that turns complex data into actionable insights

Requirements

Bachelor's Degree in Computer Science, Engineering, Physics, Math, proof of exceptional skills in related field, or equivalent experience Proficient in Python and SQL with experience building data models, performant queries, and ETLs at scale (e.g. PostgreSQL, Clickhouse, Pyspark, Dagster) Experience across the data lifecycle including sourcing, ingestion, transformation, analytics, and visualization Ability to own projects end-to-end from defining the right data to collect, building robust pipelines, to delivering actionable metrics and tooling Ability to thrive in a rapidly changing environment with high ambiguity; self-starter mentality Passion for the future of transportation and AI technologies