Data Engineer Jobs

About The Position

Requirements

• Typically requires a degree in Science, Technology, Engineering or Mathematics (STEM) and 8 years prior relevant experience or an Advanced Degree in a related field and minimum 5 years of experience.
• Demonstrated professional experience communicating in English (verbal and written).
• U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.

Nice To Haves

• Expertise in data analytics workflows, statistical methods, and engineering data interpretation, with a proven record of solving complex technical challenges.
• Advanced knowledge of machine learning (ML) concepts, with demonstrated experience in developing, deploying, and validating models for prediction, classification, and anomaly detection.
• Advanced degree in Mechanical Engineering, Aerospace Engineering, Data Science, or a related field.
• Deep understanding of mechanical engineering principles, including structural behavior, dynamics, thermal concepts, and aircraft systems.
• Strong experience with Python for data analysis (e.g., NumPy, Pandas, PySpark) and familiarity with ML frameworks such as TensorFlow or Scikit-learn.
• Experience with finite element analysis (FEA), structural analysis, thermal concepts, dynamics, or instrumentation data interpretation.
• Proficiency with database tools and SQL for managing and analyzing datasets.
• Advanced experience with data visualization tools (e.g., Tableau, Power BI) and the ability to present insights effectively to diverse stakeholders.
• Expertise in specialized engineering data such as strain gauge, thermal, or flight/aircraft performance datasets.
• Experience with Agile methodologies and tools (e.g., JIRA, Confluence) and experience in cross-functional collaboration.
• Knowledge and hands-on experience with digital thread, PLM systems, or model-based engineering workflows to drive digital transformation initiatives.

Responsibilities

• Lead and oversee the analysis of engineering and aircraft performance datasets, delivering actionable insights to improve product performance and reliability.
• Drive the development, training, and validation of machine learning (ML) models, with applications including predictive maintenance, service time estimation, and performance forecasting.
• Define and standardize validation approaches, acceptance criteria, and performance metrics for analytical and ML models across multiple programs.
• Guide and mentor junior engineers on data analytics and machine learning methodologies, fostering skill development and technical growth within the team.
• Serve as the primary technical liaison with engineering discipline owners, design teams, and external stakeholders to address critical engineering challenges and opportunities.
• Develop and implement best practices for data curation, cleaning, integration, and preparation for analytics and ML workflows.
• Oversee the analysis of strain gauge, structural, thermal, and flight/aircraft data, identifying trends, predictive indicators, and opportunities for system optimization.
• Lead collaborative efforts with design, reliability, service engineering, and customer support teams to provide data-driven recommendations that enhance product performance and address customer needs.
• Conduct advanced statistical analyses to assess quality, completeness, and integrity of engineering and enterprise data.
• Research, evaluate, and implement cutting-edge ML algorithms (e.g., supervised learning, unsupervised learning, clustering, anomaly detection) to solve engineering challenges and improve performance.
• Represent the organization in executive-level presentations, communicating technical recommendations and insights to leadership and customers.
• Develop and maintain technical documentation, presentations, and reports for technical and non-technical audiences.
• Advocate for and lead efforts in digital transformation, including leveraging digital thread, PLM systems, and model-based engineering workflows.
• Occasionally travel domestically and/or internationally to support project requirements, supplier engagements, or customer needs.

Benefits

• Medical, dental, and vision insurance
• Three weeks of vacation for newly hired employees
• Generous 401(k) plan that includes employer matching funds
• Participation in the Employee Scholar Program (ESP)
• Life insurance and disability coverage
• Employee Assistance Plan, including up to 8 free counseling sessions.