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Manufacturing Engineer; Onsite

Job in East Hartford, Hartford County, Connecticut, 06118, USA
Listing for: Raytheon
Full Time position
Listed on 2026-07-02
Job specializations:
  • Engineering
    Manufacturing Engineer, Quality Engineering, Process Engineer
Job Description & How to Apply Below
Position: Manufacturing Engineer (Onsite)

Manufacturing Engineer

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.

At Pratt & Whitney, you'll be part of an evolving, globally diverse company that's moving fast to shape the future of aviation. Customers all over the world depend on our technology and the people behind it. As part of the team at Pratt & Whitney, you'll help answer today's challenges in powered flight while shaping and supporting tomorrow's solutions.

The Hollow Fan Blade (HFB) Unit of CSMC is hiring a Manufacturing Engineer to support the monitoring and implementation of Multivariate Statistical Process Controls (MSPC) and automated Functional Assessments (FA).

What You Will Do:

  • The selected candidate will be responsible for working with Sr manufacturing engineers and the OpX Team to identify key variables that represent the performance of a process and for creating controls that alert process owners of changes in process capability.
  • The candidate will also work to develop skills necessary to be able to connect changes in component geometry to its functional performance via correlation and emulation of aerodynamic & structural physics responses.
  • You will be a leader in root cause investigations addressing challenges with low First Pass Yield (FPY), high Cost of Poor Quality (COPQ), and low throughput.
  • The selected candidate will utilize their Data Science and Statistical expertise in gathering & analyzing large datasets, deploy inductive & deductive investigative tools, and recommend solutions.
  • As a Manufacturing Engineer, the candidate's skills in operations optimization and data analytics will also be used to support other functions such as Continuous Improvement, Waste Reduction (Lean), and general business performance.
  • To execute the desired process improvement, the candidate will be responsible for project planning, collaborating with various engineering disciplines, and influencing management to implement the desired solutions.

Duties and Responsibilities:

  • Develop and Monitor Multivariate Process Controls using both traditional SPC rules and custom methods.
  • Lead root cause investigations and work with process owners to execute solution implementation.
  • Relate Key Process Inputs to Process Outputs with tools like PFMEAs or Characteristics Matrices.
  • Identify relationships between Part Geometry and Part Performance with Designed Experiments (DOE) and statistical modeling.
  • Perform ad-hoc data analysis requests to support business improvement objectives.
  • Assemble, Lead and Present Monthly MCAB (Manufacturing Corrective action Board) Meetings
  • Ensure Business Maintains Compliance to the requirements of deviations, MSPC and FA.

Qualifications You Must Have:

  • Bachelor's degree in engineering (manufacturing, mechanical, industrial, aerospace, Data Science or related field.)
  • 2+ Years of related experience
  • Proficiency in mathematical/statistical software like Minitab, JMP, or MATLAB.
  • Experience with databases/data warehouses and constructing queries
  • Strong communication and influencing skills

Preferred Qualifications:

  • Six Sigma Green Belt or Red-X Apprentice experience
  • Strong data analytics & statistical modeling skills with experience in Principal Component Analysis, Linear Regression, Partial Least Squares, and Gaussian Process Modeling.
  • Database/data warehouse and query experience with Databricks, SQL, and Python preferred.
  • Demonstrated ability to lead root cause investigations, propose corrective actions & technical solutions, and execute on the implementation of those actions.
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