DLA - Senior Engineer

Sponsorship : GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE.  DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP (e.g., H-1B, TN, STEM OPT, etc.) NOW OR IN THE FUTURE. 

Work Arrangement:

This role is categorized as hybrid. This means the successful candidate is expected to report to the office four times per week or other frequency dictated by the business.

The Role

Global Manufacturing Engineering at GMTCI is a bridge between Global Manufacturing Plants & Global Product Engineering in getting the Product & Process Right. GMTCI’s strategy is to “Execute Design / Simulation / Virtual / Engineering Workshare for the Globe + Enable Factory for the Future” 

This position of Manufacturing Data Analytics Engineer is a Mfg 4.0 initiative in ME Vehicle Systems Automation Group which is primarily responsible for applying Data Analytics techniques on GM manufacturing processes in GM manufacturing plants across the globe to solve complex manufacturing business problems with big data. In this position, the engineer supports critical business operations and decision making through creation domain data exploration, data processing pipeline, and business intelligence reports. 

This is primarily a non-travel job. Business travel will be necessary on special requirements and will be for a short duration. Depending on the need, there will be an International Short-Term assignment for 6 months in the first year for training & development. 

What You'll Do

• Collaborate with plant teams, SMEs, IT departments, and the analytics community to capture, prioritize, and document data analytics requirements, driving measurable results.  

• Extract data using existing IoT solutions and big data sources, conduct thorough analysis, perform testing, and validate outcomes.  

• Analyze datasets to identify trends and patterns, interpret and communicate insights to various teams and leaders to enhance and streamline processes.  

• Apply manufacturing domain knowledge and IoT knowledge to develop proof of concepts to address complex manufacturing challenges.  

• Propose solutions and strategies to business challenges that drive significant impact.  

• Monitor the health of data collection pipelines, report issues, and follow up with responsible teams.  

• Write user stories and frameworks for the IT development team to productize the self developed solutions.  

• Present complex information through data visualization techniques.  

• Provide training and guidance to business partners on data analysis methodologies, reporting, and tools. 

Your Skills & Abilities (Required Qualifications)

• Masters / Bachelor's Degree in Automotive technology, Mathematics, Statistics, Computer Science, or information technology. 

• 4-10 years of experience in any Automotive company or Data Analytics environment. 

• Proficient in Python (preferred) or any object-oriented programming languages. 

• Expert in data analysis, including identifying patterns, extracting valuable insights, and providing data-driven recommendations to support decision-making.  

• Proficient in applying statistical techniques, utilizing analytical tools, and AI/ML/GenAI for given business problem. 

• Experienced in working with data pipelines, PowerBI, SQL queries, Git, Databricks, Azure cloud services, and DevOps/MLOps/LLMOps. 

• Familiarity with IoT data collection methods and solutions. 

• Familiarity with automotive production processes, industrial automation, throughput analysis, and industrial engineering is considered an added advantage. 

• Ability to learn quickly and adapt to new challenges. 

• Exceptional collaboration skills and the ability to build strong relationships. 

• Process-oriented mindset with a focus on efficiency and effectiveness. 

• Outstanding project management skills within an agile environment. 

• Demonstrates creativity in problem-solving, thinking dynamically and beyond industry norms, and adapting swiftly to new technical areas. 

• Proficiency in collaborating with intercultural, multi-disciplinary, and remote teams to achieve functional objectives. 

• Strong organizational, planning, and prioritization skills, with a meticulous approach to project execution. 

• Readiness to travel across regions as necessary for project implementation.