Durability Data Analytics Principal Engineer P4 Onsite - RTX; Raytheon Technologies
Listed on 2026-09-11
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Engineering
Aerospace / Aviation / Avionics, Data Engineering, Mechanical Engineer
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U.S. Citizen, U.S. Person, or Immigration Status Requirements:
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At RTX, the world's 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.
Only candidates Internal to Pratt & Whitney Engineering will be considered for this role.
What You Will Do:Hot Section Engineering (HSE) at Pratt & Whitney is looking for a motivated, ambitious individual to join our Hot Section Durability organization in our East Hartford, CT location. The Durability Discipline is highly specialized with particular focus on advanced cooling designs, aerodynamics, heat transfer, lifing, coatings, high-temperature aerospace alloys, and manufacturing. HSE is seeking a dynamic individual to evaluate fielded performance of Hot Section products in commercial and military engines via fleetwide statistical analysis.
This candidate will need to leverage technical acumen, curiosity and attention to detail to produce robust predictions and actionable insights to drive business decisions.
- Optimize and execute ETL pipelines within Databricks to integrate structured and unstructured data from internal and external sources into the existing data warehouse
- Interrogate the data to drive insights, and incorporate advanced statistical analysis, including the adoption of AI/ML tools
- Utilize a variety of data visualization tools and techniques to present findings to technical and non-technical stakeholders
- Collaborate with cross-functional teams to identify data requirements, ensure data accuracy, and maintain data integrity across the analytics workflow
- Drive advancement, consistency, and continuous improvement of Hot Section life predictions
- Bachelor’s degree in Science, Technology, Engineering or Mathematics (STEM)
- 8 years of engineering experience, or an Advanced degree in a related field and 5 years of related engineering experience.
- Master’s Degree in Data Science or related discipline
- Proficiency in data engineering and database architecture
- Knowledge of statistical analysis techniques, especially reliability analysis
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