Internship, Data Engineer, Data Engineering & Business Intelligence (Winter/Spring2027)

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:

We are looking for a motivated Data Engineering Intern to join our growing Data Engineering & Business Intelligence team, helping build, maintain, and improve the pipelines and services that power analytics across Tesla's product lines, including Vehicles, Semi, Robotaxi, and Optimus. You'll work across our data warehouse, our internal API platform, and our AI Agent Analytics layer, using tools such as Apache Airflow, SQL Server, Vertica, Trino, Python/FastAPI, and LLM-powered analytics agents.

What You’ll Do

• Support development of LLM-based analytics agents, translating business metric requests into accurate SQL, structured configs, and clear documentation
• Assist in building and maintaining ETL/ELT jobs orchestrated via Apache Airflow
• Write and optimize SQL across SQL Server (T-SQL), Vertica, and Trino for dimension/fact table loads and reporting views
• Help build and extend internal Python APIs (FastAPI), including database connectors, caching, and async endpoints
• Support incremental/CDC-style loading patterns for fact and dimension tables
• Collaborate with data analysts and stakeholders to translate business questions into data models and metrics
• Monitor pipeline health, troubleshoot job failures, and help improve reliability
• Document pipelines, data flows, and metric definitions clearly for other engineers and analysts

What You’ll Bring

• Pursuing a degree in Computer Science, Engineering, Information Systems, Data Science, or related field (or equivalent experience) with a gradtuation date between May 2027-June 2028
• Strong foundation in SQL - writing, debugging, and optimizing queries (joins, CTEs, window functions)
• Solid understanding of Python, including basic API development concepts (REST, async/await a plus)
• Basic knowledge of ETL/ELT concepts and workflow orchestration (Airflow or similar)
• Familiarity with at least one relational database (SQL Server, MySQL, PostgreSQL, Vertica, etc.)
• Experience working with LLMs is a plus — e.g. prompt engineering, building or integrating with LLM-based agents/tools, or using LLM APIs in a project
• Strong written and verbal communication skills; comfortable working with both technical and non-technical stakeholders
• Eagerness to learn modern data engineering practices and take on increasingly complex tasks