Manufacturing Engineer – Data-Driven Operations (Preferred Locations - Waukesha, WI, State College PA, Noblesville, IN)

GE HEALTHCARE•Waukesha, WI

20d

About The Position

We are seeking a forward-thinking Manufacturing Engineer with a strong foundation in traditional manufacturing processes and a passion for leveraging data analytics to drive operational excellence. The ideal candidate will combine engineering expertise with skills in data analytics using scripts (e.g., Python, R, JMP, Minitab, VBA, SQL) and Power BI to optimize production systems, improve quality, and support digital transformation initiatives.

Requirements

Bachelor’s degree in Manufacturing Engineering, Industrial Engineering, Mechanical Engineering, or related field.
Minimum 4 years of experience in a manufacturing environment.
Experience with MES, ERP, or other manufacturing systems.
Proficiency in Power BI or similar software like Tableau, Spotfire, etc, for data visualization and reporting.
Experience with coding/scripting (e.g., Python, R, JMP, Minitab, SQL, VBA, or similar).
Strong analytical and problem-solving skills.
Familiarity with lean manufacturing, Six Sigma, or continuous improvement methodologies.

Nice To Haves

Knowledge of digital twin technologies and data integration.
Certification in Lean Six Sigma or similar.
Experience with database management.
Experience with Industry 4.0 technologies and smart factory initiatives
Open to learn new skills, especially in coding, using Python, SQL, R, PowerBI, and others.
Willing to fail to learn about potential pitfalls, and to determine possible roadblocks.

Responsibilities

Analyze manufacturing processes to identify opportunities for improvement in efficiency, quality, delivery, and cost.
Develop and implement data-driven solutions using Power BI dashboards and custom scripts to monitor and enhance production performance.
Collaborate with cross-functional teams for requirements gathering to improve reporting and data accessibility.
Support root cause analysis and corrective actions using statistical tools and data modeling.
Develop Proof of Concept Solutions to improve operations.