Internship, Data Engineer, Applications Engineering (Winter/Spring 2027)

What to Expect

Consider before submitting an application:

• This position is expected to start around January 2027 and continue through the entire Spring term (ending approximately May 2027 or later, if available). We ask for a minimum of 12 weeks, Full
• Time (40 hours/week) 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.

About the Team:

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 and BI platform within Tesla. This position offers a unique opportunity to impact the entire organization by developing data tools and creating a data driven culture.

What You’ll Do

• Design, develop, and maintain batch and streaming data pipelines that ingest, transform, and serve data in Tesla's analytics platform
• Build and optimize data models and datasets that power business intelligence, operational reporting, and analytics
• Clearly communicate analysis assumptions, methodology, limitations, and results to technical audiences
• Work with engineers and stakeholders to gather data requirements and deliver reliable, well-documented data products
• Write well-organized SQL and Python for transformations, and contribute to orchestration and distributed processing where applicable (Airflow, Spark, Kafka)
• Monitor and improve data quality, reliability, and performance of datasets and downstream systems
• Identify, analyze, and interpret trends in complex data sets to support dashboards and reports
• Drive underlying data systems improvement by working with key cross-functional stakeholders

What You’ll Bring

• Currently pursuing a degree in Computer Science, Information Technology or a related field of study and graduating between December 2026-December 2027
• Proficiency in one or more of the following developer skills: Python, Java, Go, C/C++, Ruby, SQL or other common industry languages
• Familiarity with database concepts such as MySQL, MS SQL
• Nice to have: Air Flow, Splunk, Kafka, Spark
• 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