Data Engineering Intern - AI & Analytics (January - August 2027)

Rivian and Volkswagen Group Technologies
Palo Alto, California, United StatesPosted Sep 8, 2026
Data Science / ML

About the role

About Us

Rivian and Volkswagen Group Technologies is a joint venture between two industry leaders with a clear vision for automotive’s next chapter. From operating systems to zonal controllers to cloud and connectivity solutions, we’re addressing the challenges of electric vehicles through technology that will set the standards for software-defined vehicles around the world. The road to the future is uncharted. By combining our expertise across connectivity, AI, security and more, we’ll map a new way forward. Working together, we’ll create a future that’s more connected, more intelligent, more sustainable for everyone. This is a general application used to fill multiple internship openings across our AI, Data, and Analytics teams. If selected, you will be matched to a specific team based on your background and interests during the interview process. Data Engineering Intern - AI & Analytics Data Engineering Intern - AI/ML Data Engineering Intern - Analytics Software Engineering Intern - AI & Machine Learning Software Engineering Intern - AI Platform Software Engineering Intern - DevOps Software Engineering Intern - Execution Apps Software Engineering Intern - Fleet Applications Software Engineering Intern - Vehicle and Fleet Apps Systems Analytics Engineering Intern - Connectivity and Telematics Role Summary Software-defined vehicles generate enormous amounts of data, from vehicle telemetry to manufacturing and fleet operations. As a Data Engineering intern, you will help turn that data into usable, reliable infrastructure and analytics, working on data pipelines, machine learning platforms, or the software and analytics supporting fleet and manufacturing applications. Specific project areas vary by team and may include: Developing SQL and Python based data transformation and pipeline code Building and maintaining ELT pipelines and analytics workflows on Databricks or similar platforms Supporting machine learning model development, evaluation, or deployment infrastru

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