Reliability Analytics Engineer

Amazon.com Services LLC is seeking a Reliability Analytics Engineer to blend hands-on reliability work with a strong data systems mindset. The role is onsite in Seattle, WA, with a salary range of USD 117,300 to 160,000 per year. This position concentrates on reliability data analytics, defining data pipelines, and building tools and dashboards to support reliability across Amazon Robotics fleets, scaling evaluation across multiple product programs.

Responsibilities

• Articulate data requirements and specifications for reliability pipelines, partnering with data engineering teams to design and validate ETL processes that ingest field failures, test data, and product telemetry from enterprise data lakes and EAM systems.
• Cleanse, validate, and prepare reliability datasets (including censored life data, field service records, and accelerated test results) to ensure accurate assessments before they inform engineering decisions.
• Translate reliability engineering questions into data queries and assessment workflows, converting ambiguous problems into repeatable, scalable evaluation methods that other engineers can reuse.
• Develop and maintain reliability-focused assessment tools and automation using Python, AI/ML, and statistical libraries, such as automated failure mode classification, survival assessment calculators, and fleet health monitoring scripts.
• Define dashboard requirements for reliability KPIs (availability, MTBF, MTTR, and failure rate trends); build prototypes and operationalize production dashboards.
• Identify data gaps, define collection requirements for new failure modes or test programs, and collaborate with hardware test and field teams to close data gaps.
• Establish data governance practices for reliability datasets, including metadata standards, version control, and traceability to source systems to ensure reproducible and auditable assessment findings.

Requirements

• BS degree in mechanical engineering or equivalent
• 3+ years of experience in mechanical engineering or equivalent
• Experience with data analysis tools such as Advanced Excel, SQL, Tableau, Python
• Experience applying basic statistical methods (e.g., regression) to challenging business problems

Technologies

• Python
• SQL
• Tableau
• Advanced Excel
• AWS S3
• AWS Redshift
• AWS EMR
• AWS RDS
• Reliasoft
• Minitab
• JMP
• AI/ML

Benefits

• Medical, Dental, and Vision Coverage
• Maternity and Parental Leave Options
• Paid Time Off (PTO)
• 401(k) Plan

A Day In The Life

• Run Mean Cumulative Function (MCF) and Weibull analyses on robot fleets to verify suspensions before sharing results with the reliability team.
• Collaborate with data engineers to define telemetry pipeline requirements, including required fields, censoring rules, and output schemas.
• Develop Python tools that automate reliability growth tracking from the data lake, apply models, and generate standard reports accessible to engineers.
• Provide failure rate data by subsystem to support DFMEA exercises.
• Refine machine learning classifiers that auto-tag field failure tickets by mode, improving accuracy with sustaining team feedback.
• Operate as a reliability engineer who understands repairable systems, physics-of-failure, and life data.
• Differentiate through scaling expertise by building data tools, automation, and AI that the entire team can run。

About The Team

Amazon Robotics Reliability Engineering is a multidisciplinary group of engineers united by a drive to astonish customers by solving complex optimization challenges. The team thrives on ambiguity, moves quickly, and supports one another’s growth.