Specialist, Aircraft Reliability & Predictive Maintenance

What are your contributions to the team?

The Aircraft Reliability & Predictive Maintenance team within the Connected Aircraft program is seeking a talented and business-oriented specialist to help improve fleet availability, aircraft reliability, and maintenance effectiveness across Bombardier's global fleet. 

In this role, you will combine aerospace engineering, reliability analysis, maintenance practices, and engineering analytics to identify emerging degradation trends, support condition-based maintenance strategies, and advance predictive maintenance capabilities for Bombardier aircraft. You will work closely with aircraft system specialists, customer support teams, suppliers, and data scientists to transform operational and maintenance data into actionable engineering insights. 

Analytics, Python development, and AI technologies are important tools in this role, but the primary focus is understanding aircraft systems, reliability drivers, failure mechanisms, and maintenance optimization opportunities. 

Your responsibilities will include: 

• Analyze Connected Aircraft data, including Aircraft Health Monitoring System (AHMS) and maintenance data, to identify degradation patterns, reliability opportunities, and emerging issues across aircraft systems and components 
• Investigate operational events and reliability trends to support root cause analysis and the development of corrective actions 
• Develop, validate, and continuously improve Condition Monitoring Events (CMEs) using engineering principles, operational experience, data analytics, and predictive models 
• Collaborate with aircraft systems specialists, suppliers, and service engineering teams to improve fleet reliability and product performance 
• Support the evolution of maintenance programs and condition-based maintenance initiatives, promoting the transition from scheduled maintenance to data-driven maintenance strategies 
• Act as a key liaison with Aftermarket teams, including Technical Services, the Customer Response Center (CRC), and Field Service Representatives (FSRs), ensuring operational insights are translated into practical maintenance actions 
• Monitor fleet health and provide near real-time operational support using advanced cloud-based tools and digital applications 
• Develop and maintain Python-based analytical tools, scripts, and data workflows to support fleet health monitoring and predictive maintenance initiatives 
• Work with data scientists and software development teams to integrate advanced analytics and AI capabilities into customer-facing predictive maintenance solutions 
• Document engineering analyses, predictive maintenance logic, and reliability findings using version control and engineering best practices 
• Support user enablement, training activities, and continuous improvement of Bombardier's Predictive Maintenance applications 
• Represent Bombardier in reliability, maintenance, and industry working groups related to aircraft health monitoring and predictive maintenance 

How to thrive in this role?

Preferred educational background: 

• Bachelor's degree in Aerospace Engineering, Mechanical Engineering, Systems Engineering, Reliability Engineering, Aircraft Maintenance Engineering, or a related engineering discipline 

Preferred experience: 

• Experience in aircraft systems, aircraft maintenance, aircraft reliability, or aerospace engineering 
• Knowledge of aircraft health monitoring, reliability analysis, failure investigation, or fleet performance management 
• Understanding of Line Replaceable Units (LRUs), aircraft systems architecture, and maintenance troubleshooting 
• Experience with condition-based maintenance, predictive maintenance, MSG-3 methodology, or maintenance program optimization is considered a strong asset 

Technical skills: 

• Strong analytical and problem-solving abilities 
• Experience with Python, SQL, and data analysis tools 
• Familiarity with cloud-based analytics platforms and data visualization tools 
• Ability to work with large operational and maintenance datasets 
• Experience applying statistical methods to engineering or reliability problems 

Assets: 

• Experience with machine learning, artificial intelligence, or predictive analytics 
• Knowledge of Aircraft Health Monitoring Systems (AHMS) and Connected Aircraft technologies 
• Experience working within the aerospace, aviation, defense, or transportation industries