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MR2687: Principal Quality Engineer (Data & Analytics) (Ref: 250200234)

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About SAESL

A joint venture company between Rolls-Royce Plc and SIA Engineering Company. The company first started operations in 2001 and has since become a market leader for both engine overhaul and component repair services.

As a result of the sustained business growth, SAESL has continued to expand its facilities and develop new capabilities for both its engine overhaul and component repair businesses. The Engine Overhaul business has the capability to service all products in the Trent engine family, this includes: Trent 500, Trent 700, Trent 800, Trent 900, Trent 1000 and Trent XWB; SAESL is the only Trent engine MRO that can support all product variants. The Engine Overhaul business has the capacity to repair and overhaul over 300 Trent engines per year and it is equipped with a state-of-the-art Engine Test Facility that supports our best in class engine turnaround times.

Why Join SAESL

  • Staff Benefits (Comprehensive Medical Coverage, Flexible Benefits, Company Transport)
  • Training/Career Progression Opportunities
  • Job Security

About this role

The Principal Quality Engineer (Data & Analytics) is responsible for developing and maintaining quality data governance, defect analytics, and performance measurement systems. This role ensures data-driven decision-making, risk identification, and quality improvements by providing real-time insights into defect trends, non-conformance tracking, and predictive analytics.

Job Description

Quality Data Governance & Performance Metrics

  • Define and implement data governance standards for quality metrics, ensuring accuracy and traceability of defect data.
  • Develop and maintain real-time dashboards, scorecards, and quality KPIs for leadership reporting.
  • Ensure compliance with aviation quality regulations (EASA, FAA, CAAS, AS9110, ISO 9001) in data reporting and tracking.


Defect Analytics & Predictive Modelling

  • Manage the Defect Analytics Hub, providing real-time analysis of quality escapes, rework rates, and defect trends.
  • Utilize statistical process control (SPC), AI-powered analytics, and predictive modelling to proactively identify risks.
  • Conduct data-driven root cause analysis (RCA) to support defect elimination initiatives.


Digital QMS & Automation

  • Support the implementation of digital tools for quality reporting, defect tracking, and process automation.
  • Collaborate with IT and Engineering teams to optimize QMS integrations and automate data workflows.
  • Ensure alignment of quality data with regulatory reporting and customer quality expectations.


Stakeholder Collaboration & Training

  • Provide training and guidance to Quality Engineers, Operational Leaders, and Production teams on data utilization and defect tracking.
  • Work closely with Operations, Engineering, and IT to ensure quality analytics are actionable.
  • Support customer and regulatory audits by providing data-driven insights and compliance reports. 　

Requirements

  • Bachelor’s degree in engineering, Quality Management, Data Science, Statistics, or a related field.
  • Certifications in Lean Six Sigma (Green/Black Belt), Data Analytics, or ISO 9001 Lead Auditor are advantageous.
  • 6+ years of experience in quality analytics, defect tracking, or performance monitoring in aerospace/MRO.
  • Strong experience with Power BI, Tableau, SQL, or Python for quality data visualization and predictive analytics.
  • Hands-on experience in QMS integration, KPI development, and statistical process control (SPC).
  • Data Analytics & Visualization – Expertise in defect tracking, predictive analytics, and real-time KPI dashboards (Power BI, Tableau, SQL, Python).
  • Statistical Process Control & RCA – Strong knowledge of SPC, 8D, DMAIC, FMEA, and CAPA methodologies for defect prevention.
  • Digital Transformation & QMS Automation – Skilled in optimizing QMS systems, automating defect tracking, and integrating data workflows.
  • Regulatory & Compliance Knowledge – Understanding of aviation quality standards (EASA, FAA, CAAS, AS9110, ISO 9001).
  • Cross-Functional Training & Engagement – Ability to translate complex data insights into actionable quality improvements for teams.