Quality Engineer, Data Analytics & Process Improvement (Onsite)

RTX•Columbus, GA

10d•$68,900 - $131,100•Onsite

About The Position

At RTX, the world largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Pratt & Whitney is a world leader in the design, manufacture and service of aircraft engines and auxiliary power systems and has been revolutionizing modern flight for over 100 years. Join us and help shape the future of aerospace and defense. The Columbus Blades Manufacturing Facility is at the forefront of innovation, supporting both legacy product lines and new military and commercial engine programs. As a recipient of the Large Manufacturer of the Year Award by the Georgia Department of Economic Development and the Technical College System of Georgia, we are committed to excellence and continuous improvement. We are seeking Quality Engineer, Data Analytics & Process Improvement to join our team. In addition to quality engineering expertise, this role will leverage advanced data analytics, Power BI dashboards, and data science methodologies to support decision-making, process improvement, and customer satisfaction.

Requirements

Bachelor’s Degree in Engineering, Data Science, Statistics, or related field with 2 or more years of experience in a manufacturing operations or similar environment OR a Master's degree and 1 or more year of experience OR completion of the Pratt & Whitney Quality Engineering Development Program.
Hands-on experience in quality engineering and data analysis.
Familiarity with AS9100 standards and Pratt & Whitney’s Quality Requirements.
Advanced proficiency in Microsoft Office Suite, particularly Excel.
Experience with SAP, Solumina, and Power BI for data tracking, reporting, and visualization.
Strong ability to interpret and clearly communicate complex data and quality requirements to stakeholders.
Knowledge of statistical methods, data modeling, and machine learning applications in manufacturing.
Proficiency in data science tools such as Python, R, or SQL.
Demonstrated ability to automate data collection, cleaning, and reporting processes to support continuous improvement initiatives.

Responsibilities

Facilitate and participate in process reviews to support shop capability and cost analysis.
Develop and maintain Power BI dashboards to monitor and visualize quality metrics, trends, and performance across product lines.
Analyze quality data to identify patterns, root causes of non-conformances, and areas for improvement using data science tools and techniques.
Support process certification projects, utilizing data-driven insights to implement process improvements.
Evaluate procedures and processes to ensure compliance with AS9100 standards and Pratt & Whitney quality requirements.
Collaborate with cross-functional teams to investigate non-conformances, determine root causes, and implement corrective actions.
Monitor and measure the effectiveness of corrective actions using statistical methods and predictive analytics.
Apply continuous improvement tools and methodologies (e.g., Six Sigma, Lean) to enhance operational performance in alignment with business metrics (Cost, Quality, Delivery, and EH&S).
Demonstrate a commitment to environmental, health, and safety (EH&S) programs and initiatives.