FAQs
What is the expected duration of the internship?
The internship is expected to start in May 2025 and continue through the entire Summer term (August/September 2025) or into Fall 2025 if available, with a minimum requirement of 12 weeks, full-time on-site.
Where are the internship locations?
The internship locations are in Palo Alto, CA or Austin, TX.
What is the minimum number of hours I must work each week?
Interns are required to work a minimum of 40 hours per week on-site.
Can international students apply for this internship?
Yes, international students can apply, but those with work authorization through CPT should consult their school regarding their ability to work 40 hours per week before applying.
What teams might applicants be reviewed by during the hiring process?
Applicants may be reviewed by the following teams: Energy | Autobidder, Energy | Asset Management, Energy | Service Transformation & Analytics, Energy | Service Engineering Data Analytics and Infrastructure, and Energy | Product Engineer.
What technical skills are required for this internship?
Required skills include a Bachelor's Degree in Computer Science or a related field, strong knowledge of SQL and Python, experience building data pipelines using Airflow, working knowledge of Spark and big data processing, and experience with Git or other source control software.
Will I receive any benefits as a Tesla intern?
Yes, as a full-time Tesla Intern, you will be eligible for various benefits, including medical and dental plans, 401(k) options, employee stock purchase plans, sick leave after 90 days, and more.
Is prior experience in Scala preferred or required for this internship?
Scala experience is considered a plus but is not a requirement for the internship.
Will I be involved in real projects during the internship?
Yes, interns will be included in projects that are critical to their team’s success and will work closely with their Manager, Mentor, and team.
What are the main responsibilities of the internship?
Interns will be responsible for creating and maintaining data pipelines, performing advanced SQL queries, automating reporting and data quality checks, building dashboards, and collaborating with cross-functional teams to analyze and provide insights from data.