JOB DESCRIPTION

Work Arrangement: This role is categorized as hybrid. This means the successful candidate is expected to report to the office three days per week, at minimum.

YOUR SKILLS & ABILITIES (REQUIRED QUALIFICATIONS)

• Bachelor’s degree in Mathematics, Statistics, Computer Engineering, Mechanical Engineering, or a related field.
• Minimum of 5 years of experience in automotive engineering, software development, or a related role.
• Strong understanding of statistical methods and practices.
• Solid knowledge of vehicle architectures, including the interaction of various vehicle systems and ECUs.
• Demonstrated attention to detail and accuracy in complex technical tasks.
• Excellent problem-solving and analytical skills.
• Strong collaboration and communication skills, with the ability to thrive in a team environment.
• Willingness to work on-site in any of our centers for 3 days per week.

WHAT CAN GIVE YOU A COMPETITIVE EDGE (PREFERRED QUALIFICATIONS)

• Master’s degree in Statistics or Data Science
• Experience with scripting languages such as Python for data analysis or automation.

THE ROLE:

The Data Engineering organization at General Motors is pioneering innovation and leveraging data to shape the future of mobility. We are looking for a highly motivated and detail-oriented Data Engineer to join our dynamic team. In this pivotal role, you will spearhead the performance management strategy for our next-generation control and data planes. Your expertise in vehicle architectures, statistical methods, and collaborative skills will be essential in working effectively with diverse engineering teams.

WHAT YOU WILL DO

• Monitor the performance of the control and data planes in the field using established statistical methods.
• Validate control plane configurations to ensure they are deployable, function as intended, and pose no risk.
• Ensure that configuration promotion through exposure rings adequately considers all relevant factors.
• Contribute to the continuous improvement of monitoring processes and tools.
• Participate in cross-functional team meetings, providing expertise to support overall vehicle development.
• Consolidate the monitoring strategy for both legacy and new generations of vehicle data capture.
• Collaborate with the data quality organization to establish a monitoring and reaction strategy that meets customer needs and proactively addresses potential issues.