Sr Business Intelligence Engineer, Amazon Global Data Center Ops Central Insight and Analytics Team

About the role

We are looking for a Senior Business Intelligence Engineer to build the diagnostic analytics layer for Amazon's global data center operations. You will move our analytics capability beyond reporting *what* happened to explaining *why* — identifying which factors drive metric deviation, decomposing performance into attributable components, and building the analytical frameworks that enable operational leaders to take the right action.

Responsibilities

• Build analytical frameworks to explain root causes of performance gaps and recommend corrective actions
• Work with rich operational data at scale: millions of repair tickets, rack lifecycle events, parts inventory flows, workforce scheduling data, and hardware validation results
• Translate "this metric moved" into "here's why, here's who owns each piece, here's the impact"
• Partner with operational leaders to validate findings and deliver insights that influence resource allocation, process design, and investment decisions at the VP level

Requirements

• 10+ years of performing statistical analysis experience
• Expert SQL skills — complex analytical queries across large-scale datasets (multi-system joins, window functions, statistical aggregations across petabyte-scale data)
• Strong statistical foundation — regression analysis, statistical process control, hypothesis testing, and metric decomposition applied to real business problems
• Experience building automated, reproducible analytical pipelines — scheduled systems that serve ongoing business processes at production quality
• Proficiency in Python or R for data manipulation, statistical analysis, and visualization
• Demonstrated ability to decompose complex business metrics into attributable components
• Strong written and verbal communication — ability to write diagnostic narratives and present complex analysis clearly to VP-level audiences

Qualifications

• Basic Qualifications
• Experience working directly with business stakeholders to translate between data and business needs
• Experience in operational analytics — manufacturing, logistics, field operations, supply chain, or physical infrastructure domains where you've analyzed process efficiency, failure modes, or workforce productivity
• Experience with workforce analytics — productivity measurement, skill-gap analysis, labor planning, or efficiency modeling that accounts for varying task complexity and work mix
• Experience building composite metrics or indices that combine multiple dimensions into weighted scores (similar to OEE, NPS, or operational health indices)
• Experience with multivariate analysis — identifying which factors among many are most strongly associated with performance outcomes
• Experience building decision-support tools, recommendation frameworks, or analytical playbooks — structured systems where analysis directly translates to operational action
• Familiarity with forecasting methods (time-series decomposition, trend analysis, seasonality modeling) for operational planning
• Experience building analytical frameworks adopted across multiple teams — reusable tools and methods that scale beyond individual analyses
• Experience with Amazon internal data tools (Redshift, Athena, QuickSight) is a plus for internal candidates
• Experience with data center, cloud infrastructure, or hardware operations is valuable but not required — domain knowledge can be learned; analytical rigor cannot

Preferred Qualifications

• Experience in operational analytics — manufacturing, logistics, field operations, supply chain, or physical infrastructure domains where you've analyzed process efficiency, failure modes, or workforce productivity
• Experience with workforce analytics — productivity measurement, skill-gap analysis, labor planning, or efficiency modeling that accounts for varying task complexity and work mix
• Experience building composite metrics or indices that combine multiple dimensions into weighted scores (similar to OEE, NPS, or operational health indices)
• Experience with multivariate analysis — identifying which factors among many are most strongly associated with performance outcomes
• Experience building decision-support tools, recommendation frameworks, or analytical playbooks — structured systems where analysis directly translates to operational action
• Familiarity with forecasting methods (time-series decomposition, trend analysis, seasonality modeling) for operational planning
• Experience building analytical frameworks adopted across multiple teams — reusable tools and methods that scale beyond individual analyses
• Experience with Amazon internal data tools (Redshift, Athena, QuickSight) is a plus for internal candidates
• Experience with data center, cloud infrastructure, or hardware operations is valuable but not required — domain knowledge can be learned; analytical rigor cannot

Benefits

• Comprehensive benefits including health insurance, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off
• Parental leave

Pay

$130,400.00 - $176,300.00 USD annually

Schedule

Full-time