Senior BI Engineer — Diagnostic Analytics Leader

Amazon Web Services (AWS); Seattle (WA); On-site; USD 130,000 - 176,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Job summary

Amazon Data Services, Inc. is seeking a Senior Business Intelligence Engineer to build the diagnostic analytics layer for global data center operations.

You will move analytics from reporting to explaining why, identifying drivers of metric deviations, and decomposing performance into components for action. You will partner with operational leaders to validate findings and deliver insights that influence resource allocation, process design, and investment decisions at the VP level.

Qualifications

• 10+ years of statistical analysis experience.
• Expert SQL skills with multi-system joins and window functions.
• Strong statistical foundation including regression, SPC, hypothesis testing.
• Experience building automated, reproducible analytical pipelines.
• Proficiency in Python or R for data manipulation and visualization.
• Ability to decompose metrics into attributable components and explain drivers.
• Excellent written and verbal communication for VP-level audiences.

Responsibilities

• Scope analytical problems and build decomposition frameworks.
• Partner with operational leaders to validate findings.
• Deliver insights that influence resource allocation and investment decisions.
• Work with large-scale operational data to identify root causes and corrective actions.

Skills

Statistical analysis

SQL proficiency

Statistics fundamentals

Automated pipelines

Python/R

Metric decomposition

Communication

Tools

Redshift

Athena

QuickSight

Job description

Amazon Data Services, Inc. is seeking a Senior Business Intelligence Engineer to build the diagnostic analytics layer for global data center operations.

You will move analytics from reporting to explaining why, identifying drivers of metric deviations, and decomposing performance into components for action. You will partner with operational leaders to validate findings and deliver insights that influence resource allocation, process design, and investment decisions at the VP level.