Reliability Engineer, Global Reliability Intelligence Programs

Amazon Amazon · Big Tech · LU, Luxembourg · Fulfillment & Operations Management

Reliability Engineer focused on RCA and FMEA to identify and eliminate failure causes, improve uptime and performance, and proactively identify risks through FMEA. Analyzes data to identify trends and systemic issues, builds BI dashboards, and drives cross-functional execution of reliability improvements. Collaborates with DevOps teams to enhance RCA/FMEA tools.

What you'd actually do

  1. Lead Root Cause Analysis (RCA) for high-impact and recurring failures, driving deep-dive investigations to identify true root causes and ensure effective, lasting corrective actions
  2. Develop, maintain, and continuously improve Failure Modes and Effects Analysis (FMEA) to proactively identify risks, prioritize mitigation, and prevent future failures
  3. Analyze equipment and operational data to identify trends, systemic issues, and performance gaps, translating findings into actionable reliability improvements
  4. Build and maintain BI dashboards, automated reports, and performance metrics (e.g., uptime, MTBF, failure rates) to enable data-driven decision-making
  5. Lead cross-functional execution of reliability improvements by partnering with operations, engineering, maintenance, and external vendors across multiple sites and regions

Skills

Required

  • Microsoft Excel (advanced)
  • SQL
  • Python
  • R
  • BI analytics tools
  • Tableau
  • AWS QuickSight
  • Cognos
  • MS Power Query
  • Root Cause Analysis (RCA)
  • Failure Modes and Effects Analysis (FMEA)
  • Predictive and preventative maintenance
  • Troubleshooting
  • DevOps
  • Serverless
  • Software development and design
  • CI/CD
  • Storage
  • Networking
  • Databases
  • Infrastructure automation
  • API-enabled environment
  • Agile development
  • Software architecture/patterns
  • Cloud services
  • Written and verbal communication
  • Presenting technical information

Nice to have

  • SAS
  • Matlab
  • Perl
  • AWS
  • API design
  • Cloud architecture/deployment
  • Service-oriented architecture
  • Mobile development
  • Performance optimization
  • Database design
  • Data modeling
  • Data pipeline design
  • Full software development life cycle
  • Coding standards
  • Code reviews
  • Source control management
  • Build processes
  • Testing
  • Operations
  • System architecture
  • Scalability
  • Reliability
  • Performance in a database environment
  • Quant research methodologies
  • Qual research methodologies
  • 1P data analysis
  • 3P data analysis
  • Trend analysis
  • Forecasting
  • Machine learning algorithms
  • Business-critical pattern identification
  • New metric development
  • Finance process automation
  • Business process automation

What the JD emphasized

  • Knowledge of Microsoft Excel at an advanced level
  • Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)
  • Knowledge of BI analytics, reporting or visualization tools like Tableau, AWS QuickSight, Cognos or other third-party tools
  • Experience working with large-scale data mining and reporting tools (i.e. SQL, MS Power Query, Python), or experience in building financial and operational reports/data sets that inform business decision-making
  • Experience using data to drive root cause analysis for making business decisions with Excel or other analytical tools
  • Experience with predictive and preventative maintenance, repair, troubleshooting, and diagnostics on material handling equipment (MHE) and automated conveyor systems
  • Experience in at least one of these technology areas: DevOps, serverless, software development and design, CI/CD, AI/ML, Storage, Networking or Databases
  • Knowledge of infrastructure automation delivered through the software development lifecycle in an API-enabled environment, including agile development, software architecture/patterns, and modern cloud services
  • Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders