About the Role
Global Data Center Operations (GDCO) is seeking a Sr. Technical Program Manager, Continuous Improvement to lead enterprise-wide process optimization across data center operations. In this role, you will apply advanced statistical methods, Lean and Six Sigma methodologies, and AI-driven analytics to eliminate waste, reduce variability, and accelerate capacity delivery at global scale.
You will serve as the single point of contact (SPOC) for process optimization across DCO - translating operational data into executive-ready insights that directly influence VP and SVP-level decisions on resource allocation, tool investment, organizational design, and capacity trade-offs. You will also design and scale a continuous improvement education program for ~100 Cluster Operations Leads building a distributed network of process-literate leaders who can identify and execute improvement opportunities within their clusters without central dependency.
This role is based in Seattle, WA and requires up to 50% travel to MLZ Data Centers nationwide
Key job responsibilities
Statistical Process Control & Advanced Analytics: Apply statistical tools and AI capabilities to isolate root causes of variability in capacity delivery, repair cycle times, and workforce productivity - transforming operational intuition into quantifiable, defensible decision inputs.
Process Optimization & Waste Elimination: Lead enterprise-wide identification and elimination of non-value-added steps across capacity delivery, repair, and logistics workflows using Lean and DMAIC methodologies to compress cycle times and reduce cost-per-rack.
VP/SVP-Level Influence & Strategic Advisory: Translate operational data into executive-ready insights and investment recommendations, directly influencing senior leadership decisions by quantifying the cost of inaction and projected ROI of process interventions.
Lean & Six Sigma Education at Scale: Design and deliver a structured curriculum covering Lean principles, Six Sigma methodology, defect elimination, waste reduction, and statistical thinking for ~100 Cluster Operations Leads
Work Complexity Reduction: Identify, quantify, and eliminate non-physical-touch work and administrative burden from technician queues through value stream mapping and statistical analysis of touch-time ratios, reallocating skilled labor capacity toward high-value hands-on delivery.
Global Process Standardization: Drive adoption of standardized workflows and directed work across all regions, ensuring consistent execution regardless of site, cluster, or operator tenure.
Capacity Delivery Velocity: Partner with delivery leaders to apply constraint theory, statistical process control, and variation analysis to install-driven bottlenecks - reducing variability and improving on-time handoff rates across core and Gen AI platforms.
Continuous Improvement Governance & Operating Model: Establish and govern the CI operating system (Kaizen events, value stream maps, tollgates, control plans, project pipelines) across GDCO, embedding improvement discipline into operational cadence rather than treating it as episodic project work.
BASIC QUALIFICATIONS
- 10+ years of program or project management experience
- Master's degree or MBA in Industrial Engineering, Operations Research, Business Operations, Supply Chain, or a related quantitative field.
- Master Black Belt in Six Sigma
- 5+ years of experience using statistical/quantitative methods (regression analysis, hypothesis testing, control charts, variation analysis) to diagnose root causes and drive measurable operational improvements - with documented outcomes
- 3+ years of experience designing and delivering process improvement training or education programs to 50+ participants (manager-level or above), covering Lean, Six Sigma, or equivalent CI methodologies
PREFERRED QUALIFICATIONS
- Experience implementing repeatable processes and driving automation or standardization
- Experience leading continuous improvement programs across a globally distributed organization including establishing governance structures such as Kaizen cadences, tollgate reviews, and CI project pipelines.
- Experience applying AI/ML-driven analytics (predictive modeling, anomaly detection, NLP) to operational datasets to surface improvement opportunities beyond traditional SPC methods.
- Familiarity with data center operations, capacity delivery, or large-scale infrastructure environments, including rack installation, repair logistics, or server deployment workflows.
- 3+ years of experience directly influencing VP-level or above leadership on resource allocation, investment decisions, or organizational design through data-driven business cases, including quantified ROI and cost-of-inaction analyses.
- Ability to travel 50% of the time
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 177,000.00 - 239,400.00 USD annually
