Reliability Analytics Engineer, Amazon Robotics

Amazon Amazon · Big Tech · North Reading, MA · Hardware Development

This role focuses on reliability analytics within Amazon Robotics, leveraging AI/ML and data engineering to build and maintain assessment tools, data pipelines, and dashboards for robot fleet availability. The engineer will perform data cleansing, prepare reliability datasets, translate engineering questions into data queries, and develop automation for failure mode classification and fleet health monitoring.

What you'd actually do

  1. Define data requirements and specifications for reliability pipelines; partner with data engineering teams to build and validate ETL processes that ingest field failures, test data, and product telemetry from enterprise data lakes and EAM systems.
  2. Perform data cleansing, validation, and preparation of reliability datasets (censored life data, field service records, accelerated test results) to ensure assessment correctness before use in making engineering choices.
  3. Translate reliability engineering questions into data queries and assessment workflows structuring ambiguous problems into repeatable, scalable evaluation methods that other engineers can reuse.
  4. Develop and maintain reliability-specific assessment tools and automation using Python, AI/ML, and statistical libraries (e.g., automated failure mode classification, survival assessment calculators, and fleet health monitoring scripts)
  5. Design and specify dashboard requirements for reliability KPIs (availability, MTBF, MTTR, failure rate trends); build prototypes and operationalize production dashboards.

Skills

Required

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

Nice to have

  • Knowledge of data engineering pipelines, cloud solutions, ETL management, databases, visualizations and analytical platforms
  • Experience with AWS services including S3, Redshift, EMR and RDS
  • Experience managing and deploying ML products
  • Experience with reliability tools (Reliasoft, Minitab, JMP, or equivalent)

What the JD emphasized

  • reliability data analytics
  • AI and automation
  • reliability-specific assessment tools
  • scaling expertise through data tools, automation, and AI

Other signals

  • Develop and maintain reliability-specific assessment tools and automation using Python, AI/ML, and statistical libraries
  • Refine Machine Learning classifiers that auto-tag field failure tickets by mode, improving accuracy from sustaining team feedback
  • Your differentiator is scaling expertise through data tools, automation, and AI—building systems the entire team can run.