Data Engineer, Fleet Analytics

Data is deeply embedded in the product and engineering culture at Tesla. We rely on data – lots of it – to improve autopilot, to optimize hardware designs, to proactively detect faults, and to optimize load on the electrical grid. We collect data from each of our cars, Superchargers, and energy storage devices to make these products better and our customers safer.

We're the Fleet Analytics team, a central team that helps many teams leverage the data we collect. We help engineers through direct support by doing data analysis for them and through applications and tools so they can self-serve those analyses in the future. To do so, we leverage our internal data platform built on top of AWS, S3, Spark, Trino using open-source data science tools such as Jupyter notebooks, Pandas, Bokeh, Superset, and Airflow.  Our work has a direct impact on Tesla's product and enables the work of hundreds of engineers across disciplines throughout the company.

We're looking for a talented engineer to own the full breadth of Data Engineering, data analysis, and data science activities for one of our partner engineering teams.  You will leverage Tesla's wealth of device data and a first-principles approach to problem solving to inform future hardware and firmware designs, as well as ensuring that our existing vehicles, chargers, and energy devices continue to perform to Tesla's exacting standards.  In this embedded role you will partner with a team focusing on another discipline (e.g., mechanical engineering, electrical engineering, or firmware engineering), joining their projects to help define product requirements, optimize control algorithms, or otherwise improve the product quality.  You will also work with other members of Fleet Analytics for peer reviews, technical growth, and to build sophisticated tools and infrastructure for working with device data.  These tools will be used across the team to improve our efficiency and shared with the rest of the company so that those we do not directly support still benefit from our work.

• Strong proficiency in Python, SQL, and building data visualizations
• Strong foundation in statistics
• Experience writing software in a professional environment
• Strong problem-solving skills to help refine problem statements and figure out how to solve them with the available data
• Curious and driven to solve complex problems
• Smart but humble, with a bias for action
• Experience with Scala a plus