Senior BI Engineer: Diagnostic Analytics for Global Ops

Amazon Web Services (AWS); Seattle (WA); On-site; USD 130,400 - 176,300; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Data Services, Inc. in Seattle seeks a Senior Business Intelligence Engineer to build the diagnostic analytics layer for its global data center operations.

You will push analytics beyond history to explain why metrics deviate, identify factors, and decompose performance for actionable guidance at the VP level. You will work with massive data: repair tickets, rack events, inventory flows, workforce scheduling, and hardware validation, delivering scalable, production-grade analytics

Qualifications

• 10+ years of performing statistical analysis experience.
• Expert SQL skills — complex analytical queries across large-scale datasets.
• Strong statistical foundation — regression analysis, SPC, hypothesis testing.
• Experience building automated, reproducible analytical pipelines.
• Proficiency in Python or R for data manipulation and analysis.
• Demonstrated ability to decompose complex metrics into components and ownership.
• Strong written and verbal communication for VP-level audiences.

Responsibilities

• Build the diagnostic analytics layer for global data center operations.
• Explain root causes and attribute performance to specific factors.
• Decompose metrics and translate findings into actionable recommendations.
• Partner with operational leaders to validate findings and drive decisions at the VP level.

Skills

Statistical analysis

SQL expertise

Statistics

Data pipelines

Python/R

Metrics decomposition

Communication

Tools

Redshift

Athena

QuickSight

Job description

Amazon Data Services, Inc. in Seattle seeks a Senior Business Intelligence Engineer to build the diagnostic analytics layer for its global data center operations.

You will push analytics beyond history to explain why metrics deviate, identify factors, and decompose performance for actionable guidance at the VP level. You will work with massive data: repair tickets, rack events, inventory flows, workforce scheduling, and hardware validation, delivering scalable, production-grade analytics