Manager, Automation Engineering

Walmart · Retail · Bentonville, AR

Manager of Automation Engineering focused on scaling and optimizing a 30K automation initiative in retail fulfillment. The role involves owning automation performance management, defining acceptance criteria for new systems, identifying performance loss opportunities, supporting root-cause analysis, and building tools for insights and decision-making. It requires strong analytical skills with SQL and Python, experience with BI tools, and the ability to translate technical findings into actionable insights for various stakeholders. The role also mentions leveraging AI to accelerate design and build agents for analytics.

What you'd actually do

  1. Instrument and analyze performance: define, validate, and monitor KPIs such as OEE, pick rate, tote cycle time, queue latency, downtime, wait time, perfect order, nil pick, OTP, and system health; build trend and insight reporting that surfaces actionable opportunities.
  2. Support system acceptance: define acceptance testing plans, success criteria, and vendor-specific automation potential and acceptance goals across throughput, cycle time, quality, uptime, and operational readiness.
  3. Find and help eliminate performance loss: partner with site, vendor, and cross-functional teams to perform structured root-cause analysis using operational data, automation studies, telemetry, and field observations; support corrective actions and verify impact.
  4. Partner on vendor expectations: translate system specifications into measurable SLAs, scorecards, and release gates; help run performance reviews and track issue follow-through.
  5. Indentify System Performance efficiency initiatives: design experiments, evaluate bottlenecks, and help standardize best practices across automation sites.

Skills

Required

  • SQL
  • Python
  • BI/reporting tools (e.g., Power BI)
  • Root-cause analysis
  • Continuous improvement methods
  • System performance analysis
  • KPI definition and monitoring
  • Data analysis
  • Dashboard development
  • Operational performance investigation
  • Bachelor's degree in Engineering, Data Science, Analytics, Statistics, Business Math, Operations Research, or related quantitative field

Nice to have

  • AI enthusiast
  • Leveraging emerging technologies
  • Building telemetry pipelines
  • Real-time dashboards
  • Alerting and observability tools
  • Data science
  • Data modeling
  • Data engineering
  • Simulation
  • Digital-twin
  • Capacity modeling
  • Retail or e-commerce fulfillment experience

What the JD emphasized

  • 3+ years of experience in automation, industrial engineering or data science with a strong focus on system performance, throughput, cycle time, quality, and acceptance.
  • Experience owning or supporting system acceptance, performance qualification, and release-readiness criteria for automated systems.
  • Strong expertise in root-cause analysis and continuous improvement methods
  • Strong analytical capability with SQL, Python, and BI/reporting tools (for example Power BI) to investigate operational performance, validate KPI logic, and turn complex data into actionable insights.
  • Experience building or supporting dashboards, recurring scorecards, or insight tools used by operations, engineering, or leadership teams.

Other signals

  • automation engineering
  • performance management
  • data analysis
  • KPI definition
  • tool building
  • retail fulfillment