Internship, Data Engineer, Energy Engineering (Winter / Spring 2026)

What to Expect

Consider before submitting an application :

This position is expected to start around January 2026 and continue through the Winter / Spring term (ending approximately May 2026) or continuing into Summer 2026 if available and there is an opportunity to do so. We ask for a minimum of 12 weeks, full-time and on-site, for most internships. Our internship program is for students who are actively enrolled in an academic program. Recent graduates seeking employment after graduation and not returning to school should apply for full-time positions, not internships.

International Students : If your work authorization is through CPT, please consult your school on your ability to work 40 hours per week before applying. You must be able to work 40 hours per week on-site. Many students will be limited to part-time during the academic year.

The Internship Recruiting Team is driven by the passion to recognize and develop emerging talent. Our year-round program places the best students in positions where they will grow technically, professionally, and personally through their experience working closely with their Manager, Mentor, and team. We are dedicated to providing an experience that allows the intern to experience life at Tesla by including them in projects that are critical to their team's success.

The Tesla Energy Products Field Quality team is looking for a passionate and collaborative Data Engineer to join the team and leverage data and analytics to ensure the best customer experience and fleet reliability across the Tesla Energy portfolio; Industrial, Residential, Supercharger, and Solar. In the Energy Products Field Quality Data Engineering role, you will identify fleet-wide part performance trends, operation, and maintenance challenges across the growing fleet of energy products. The Fleet Data Engineer's primary role is to leverage real-world performance and maintenance data to drive fleet-wide improvements by identifying trends and determining effective strategies to improve key fleet health metrics. This position is well suited for curious, inventive, and adventurous Engineers who want to solve problems with data and aren't afraid to venture into the unknown and untested when required. As part of the team, you will be enabled to work across the organization to solve problems and ensure the success of our products working alongside Industrial Energy, Residential Energy, and Solar Product & Design Engineers. Our teams operate with a non-conventional philosophy of inter-disciplinary collaboration. Each member of the team is expected to challenge and to be challenged, to create, and to innovate. We're tackling the world's most difficult and important problems-and we wouldn't succeed without our shared passion for making the world a better place.

Location : Palo Alto, CA

What You'll Do

Perform statistical analysis to quantify reliability risks in the field and identify emerging trends

Utilize fleet data for diagnostics and prognostics

Perform correlation studies between manufacturing data and field performance to develop screening tests

Maintain data pipelines / tables & applications within the Field Quality team

Create data visualizations to communicate analysis results and drive decision making

What You'll Bring

Currently pursuing a Degree in Computer Science, Physics, Electrical Engineering or related field

Strong Python, especially in a data analytics / science capacity where pandas / numpy are used heavily (matplotlib / seaborn / plotly / etc.)

Experience with multiple data architecture paradigms (SQL, NoSQL, Kafka, Spark)

Knowledge of various data communication protocols (REST API, Websockets)

Experience with version control (Git)

Familiarity with continuous integration pipelines (Docker, Jenkins, Kubernetes)

Strong analytical skills and knowledge of applied statistics including predictive analytics, time series analysis and machine learning. Working knowledge of reliability statistics such as Weibull Analysis preferred

Able to visualize data effectively

Python (matplotlib / seaborn / plotly / etc.)

Tableau (or, similar BI tools)

Any opensource / freeware viz tools (e.g., D3, ggplot)

Ability to quickly learn new technologies

Compensation and Benefits Benefits

As a full-time Tesla Intern, you will be eligible for :

• Aetna PPO and HSA plans >

2 medical plan options with $0 payroll deduction

Expected Compensation $20.00 - $50.00 / hour + benefits

Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.