Quality Engineer, Data Analytics & Process Improvement; Onsite

What You Will Do

• 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 (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.

• 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.

RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other applicable state or federal protected class.