FG-AM-61 Software Engineer Coop Fall 2026 (AI/Data) at BMW Group

Greenville, South Carolina, United States -

Full Time

Start Date

Immediate

Expiry Date

04 Jun, 26

Salary

0.0

Posted On

06 Mar, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Scientists, Data Engineers, Big Data Cluster, Cloud Solution, AI Tools, Visualisation Platforms, Data Pipeline Architecture, Data Sets, Process Improvements, Automation, SQL, AWS, Analytics Tools, Jira, Confluence, Terraform Scripts

Industry

Motor Vehicle Manufacturing

Description

A good student experience is never hands-off. We are dedicated to fostering a dynamic learning environment where students actively engage in practical experiences throughout their time with us. From the beginning, students are entrusted with specific responsibilities, ensuring they play a significant role in their learning journey. As valued team members, students are also encouraged to share and implement their own ideas, enhancing both their personal growth and the collective success of the team. Description: This position will work with Data Scientists and Data Engineers for the production implementation of multiple use cases for our Big Data Cluster on-prem as well as our Big Data cloud solution. This position also works closely with AI tools in both execution and creation of new use cases. This position also can work with our Visualisation platforms using both the data and AI tooling to create visuals for the business. The qualified intern should expect to contribute & improve in the following functions: Support the creation and maintenance of data pipeline architecture. Assist in the assembly of large complex data sets that meet functional business requirements. Identify, design, and implement internal process improvements: automating manual processes, optimizing data deliver, re-designing infrastructure for greater scalability, etc. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. Keep our data separate and secure across different business organizations. Work with data and analytics experts to strive for greater functionality in our data systems. Communicate with other team members and customers with tools such as Outlook, skype, and teams. Update and track tasks with tools such as Jira and confluence. Migration from On-Prem to Cloud Data Hub: The migration to Cloud is planned for Q2 2020. This involves, data ingestion into cloud using terraform scripts, glue catalog, glue jobs, depersonalization APIs and creating views in cloud for end user consumption. HR Use Cases: Several data assets are required to be ingested into cloud, the data transformation activities are required to prep the data for reporting. The reports must be integrated with the Cloud Data Hub. Qualifications: Possess a minimum cumulative GPA of 3.0 (not just in major) Have enrolled student status at an accredited four-year college or university in the United States. Completed at least 30 credit hours at time of application. Ability to work full-time on-site (40 hours / week). Transfer students must have a GPA from current university. MUST ATTACH A COPY OF UNOFFICIAL TRANSCRIPT Complete and pass a substance abuse test before the work term. THE WORK TERM DATES ARE August 10th - December 11th, 2026. Must be an enrolled student during all three rotations. BMW Manufacturing Company is an equal opportunity employer. It is the policy of BMW MC to provide equal employment opportunity (EEO) to all qualified persons regardless of age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.

Responsibilities

This role involves working with Data Scientists and Data Engineers on the production implementation of Big Data use cases, both on-premise and in the cloud, while closely utilizing and creating new AI tools. Responsibilities include supporting data pipeline architecture, assembling complex data sets, automating processes, and building infrastructure for data extraction, transformation, and loading.