Internship, Data Engineer, Applications Engineering (Winter/Spring 2024)

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.

Internship Program at Tesla

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.

About the Team

Tesla is seeking highly motivated software engineering students who are interested in the growing field of Data Engineering. At their core, our data engineering teams are made up of software engineers and data scientists who are excited by Big Data and how to utilize it for business functions. They help guide the company by distilling massive amounts of information and turning it into actionable strategies.

Location(s):

Fremont, CA

Austin, TX

Sparks, NV

• Data Engineering: The Data Engineering team is building a state-of-the- art analytics platform for business and operation intelligence. At Tesla, we have enormous amounts of data and we want to give meaning to it and help business users to make data driven decisions. Our platform will allow users to answer "what", "when" and "how" questions as well as allow them to ask "what if?” Interns will help design, develop, maintain and support our Enterprise Data Warehouse & BI platform within Tesla. This position offers a unique opportunity to impact to the entire organization by developing data tools and creating a data driven culture.

• Data Platforms: 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. This a small but fast-growing team which is building and operating the big data platform for the company. We collect massive amounts of IoT data, provide storage, access, and high-volume processing. Your work will affect many hundreds of Tesla engineers daily, as well as improve the functionality of our cars, chargers, and batteries worldwide.

• Energy Analytics: The Energy Analytics team uses data analytics to bridge the engineering, service, and deployment of Tesla’s charging infrastructure and to enhance the charging experience worldwide. With over 18,000 Superchargers and several thousand destination charging sites around the world, Tesla’s charging infrastructure aims to accelerate the world’s transition to sustainable transportation by enabling electric mobility without compromises.

• Fleet Analytics: The Fleet Analytics team supports and enhances products through the use of data science and data analytics tools. This team brings together data scientists and software engineers from across the company to foster collaboration, efficiency and to advance the best engineering and data analytics practices in the analytics community.

• Proficiency in one or more of the following developer skills: Python, Java, Go, C/C++, Ruby, SQL or other common industry languages
• Excellent grasp of fundamental computer science concepts and ability to write well-organized code
• Eagerness to collaborate cross-functionally with other engineering teams while able to work independently; detail-oriented and execution focused
• Currently working towards a BS, MS, or advanced degree in a relevant engineering program such as Computer Science, Computer Engineering, or Electrical Engineering
• Nice to have for Data Platforms: Kafka, ETL, IoT telemetry experience, Site Reliability experience
• Familiarity with database concepts such as MySQL, MS SQL
• Nice to have for Data Analytics: AirFlow, Splunk, Kafka, Spark