Amazon
Reliability Engineer, Global Reliability Intelligence Programs
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Reliability Engineer, Global Reliability Intelligence Programs
Reliability Engineer (RCA & FMEA) – UK
Location: Industrial Hub, Travel Required
About the Role
A Reliability Engineer focused on Root Cause Analysis (RCA) and Failure Modes and Effects Analysis (FMEA) hunts down the true causes of failures and eliminates systemic risks before they disrupt operations. This role requires leadership in high-impact investigations, data-driven decision-making, and driving measurable improvements in uptime, performance, and preventative reliability strategies.
Work includes:
- Leading deep-dive investigations to uncover root causes and deliver lasting corrective actions
- Developing and maintaining proactive FMEA frameworks to predict and mitigate risks early
- Analyzing equipment, operational, and failure data to spot trends, inefficiencies, and performance gaps
- Collaborating cross-functionally (engineering, maintenance, operations, vendors) to standardize reliability solutions
Travel intensity: Up to 50% (regional/local sites).
Eligible candidates enjoy solving complex problems, influencing strategic decisions, and delivering large-scale improvements. If you thrive in dynamic environments where reliability-breaking failures turn into knowledge-based preventions, this is your opportunity.
Key Responsibilities
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Investigation & Analysis
- Lead RCA (Root Cause Analysis) for high-impact failures, including cross-functional troubleshooting and data-driven diagnostics
- Drive recurring failures to resolution through systematic testing, process audits, and corrective actions
- Implement oral/ written RCA standards to ensure consistency and thoroughness
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Proactive Risk Management
- Develop, maintain, and enhance FMEA (Failure Modes and Effects Analysis) workflows
- Proactively identify root cause trends and severity levels in equipment, systems, or logistics operations
- Prioritize high-risk high-impact FMEAs and drive evidence-based prioritization within constraints
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Data & Dashboarding
- Build and update BI dashboards and automated reliability reports (uptime %, MTBF, failure frequency, etc.)
- Leverage SQL, data mining, and advanced statistical methods to identify trends and systemic gaps
- Prepare actionable insights from raw data that align with operational and strategic goals
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Collaborative Execution
- Partner regularly with operations, engineering, maintenance, and external vendors
- Facilitate multi-site or cross-regional initiatives to scale reliability improvements consistently
- Lead reliability teams through global implementation and continuous improvement events
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Tools & Automation
- Work with DevOps, technical teams, or external agencies to improve invention RCA/FMEA software
- Help align tool purchasing, deployment, and adoption with company standards
- Publish standard reliability documentation for Pearson departments
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- Compliance & Advocacy
- Define and promote ANSI/PEAS (Philippines Essals Systems) technical standards and compliance
- Recommend reliability-focused training programs for peers across the business
A Day in This Role
You’ll intimately partner with DevOps teams to refine scale RCA/FMEA systems, balance leadership spotlights, tactical troubleshooting, and operational improvement sprints. Core accountability shifts though themes similar to:
- Diagnostic CoffeeHours: Co-present "The Five Whys" for case studies, evaluate value of RCA/corrective action path.
- Trend Modeling: Observe and forecast recovery rates and fail-recover times; align to Hollister CV-related metrics.
- FMEA Sprint: Identicians excess risks or potential in new systems, works with external resources to model mitigation strategies.
- Vendor Review: Audit failure-handling TAMs to meet Pearson DAS standards.
- Methodology Advocacy: Shape Amazon Reliability Directives for capacity teams or share expertise in ad-hoc troubleshooting incidents.
Basic Qualifications
Education & Technical Skills
- Bachelor’s degree (or advanced high-school diploma with work experience is evaluated on a case-by-case basis)
- Strong proficiency in advanced Excel (pivot tables, macros, VBA, complicated formulae, combination of
index/match/vlookup) - Working knowledge of data scripting (e.g., SQL, Python, or R) OR analytical software (e.g., SAS, Matlab) preferred
- Background in engineering, computer science, mathematics, robotics operations research or other STEM disciplines (If applicable, AS degree with direct scripting/data analysis experience also welcome)
- Experience in root cause-driven predictive or preventative maintenance for material handling equipment (MHE) or automated conveyor systems
- Hands-on experience with Big Data reporting/mining for business decisions (use/experience of Power BI Tableau, AWS QuickSight, Cognos, Python-based reports/automation)
- Experience using sql queries or scripting to mine data for high-value insights (columnar databases, NoSQL, etc.)
Technical Experience
- Understand API-enabled systems (network and CSP validation account setup)
- Understand automated industrial operation control and cloud migration pipelines with AWS F'Ang-K-latest
- Get insights from large amounts of structured/unstructured data using SQL/ETL or equivalent
- Deep experience with CI/CD pipelines (DevOps, service development cycles, packaging interaction)
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Communication & Soft Skills
- Clear, persuasive storytelling w/ executive decision-makers and cross-functional teams
- Builds consensus among engineers external stakeholders from technical details
- Bridges divides between domain experts/facility ops, pushing aside operational silos
Preferred Qualifications
Advanced Technical Expertise
- Bachelor’s degree, bootcamps, or certifications in **cloud-based system architecture, RESTful APIs, database design scaling, or system high availability plural stack implementation environments)
- Advanced knowledge of Data Modeling or machine learning (\textit{e.g.}, pattern detection from tuning **failure occurrence aggregate timestamped batches}")
- Exposure to AI/ML pattern detection in operational data, financial forensic investigations, or predictive analytics applications
Advanced Automation & Development Experience
- Full Software Development Life Cycle (SDLC), including collaborative code reviews, source control (Gitlab/GitHub+argocd), and scaling architecture design validation
- Experience with network troubleshooting tools (telnet, nslookup, packet capture Pre-number VPN tunnel diagnose, etc.)
Impact Through Data-Driven Improvements
- Experience applying Bayesian inference in reliability studies
- Expertise in violin charts, histogram SPC for failure distributions
- Start-up abroad or technology-focused OP/plant implementation: risk forecasting in externalized consumer data streams
- Electrical/electronic fault diagnosis/test/journal management via decade-tier PHL instruments
Bonus Areas
- Ideation of new metrics benchmarks for operational maturity benchmarking (MTBF averages, post-failure resolution rates)
- Research methodology experience: labor component tracking, failure attributions (PCN73 alteration by power system clustered production line)
- Experience collaborating with third-party contractual networks for tech integration, rollout execution
Safety Statement
Amazon is an equal opportunity employer. We fully consider candidates based on skills and experience without invoking discrimination. Please review our privacy pages (https://amazon.jobs/en/privacy_page) for disclosure of personal data.
Amazon provides convenient job accommodations for candidates with disabilities. If you need any assistance during the application or hiring process, please visit: https://amazon.jobs/content/en/how-we-hire/accommodations.
Amazon UK Services LTD. respects your security, service reliability, and workplace inclusion.
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