Data Engineering Intern - AI & Analytics (Summer 2027) at Rivian and Volkswagen Group Technologies in Palo Alto, CA

Job description

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 infrastructure • Contributing to software for fleet management or manufacturing execution applications that depend on reliable data • Building automated data quality tests and integrating with CI/CD workflows Responsibilities • Design, build, or maintain data pipelines, analytics workflows, or ML supporting infrastructure • Write Python and SQL code to process, transform, and validate data • Collaborate with data scientists, analysts, or software engineers to meet data or platform needs • Contribute to automated testing for data quality and pipeline reliability • Document your work and share progress with your team throughout the internship Qualifications Minimum: • Currently enrolled in a Bachelor's or Master's program at an accredited US university • Proficient in Python and SQL Preferred: • Actively pursuing a degree in Computer Science, Mathematics, Data Science, or a closely related field, with intent to return to school after the internship • Coursework or project experience with data engineering, analytics, or machine learning • Familiarity with cloud data platforms such as Databricks, Snowflake, or Google BigQuery • Exposure to data transformation tools such as dbt, or infrastructure as code tools such as Terraform • Interest in applying data skills to vehicle, fleet, or manufacturing use cases Total Rewards We build the exceptional — and we believe the people doing that work should be rewarded accordingly. In addition to a competitive base salary, full-time positions may be is eligible to participate in our annual company performance bonus program. Payments are discretionary and not guaranteed; actual amounts depend on company results and the terms of the plan in effect, and require active employment at the time of payout. This role is also eligible for equity in the form of Restricted Stock Units (RSUs), subject to board approval and the terms of our equity incentive plans, including applicable vesting requirements. In addition to our comp