Amazon.com Services LLC

Business Intelligence, Business Intel Engineer, transportation and logistics

SeniorBusinessIntelligenceEngineer

$130–176k Bellevue, Washington, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Business Intelligence Engineer at Amazon.com Services LLC. Skills: Business Intelligence, Data Analytics, BI Tools, Data Pipelines. Own analytics strategy. Design measurement systems”

What You'll Achieve.

Guide investment decisions; Guide product roadmaps; Guide operational performance; Reduce time-to-insight; Enable faster decision-making; Maximize return on effort; Reduce lead-times

Industry & Context.

Business Intelligence, Business Intel Engineer, transportation and logistics
Problems you'll solve

Turning ambiguity into action; Sizing opportunities; Prioritizing opportunities; Deep-dive investigations

What They're Looking For.

Must Have

10+ years relevant experience, 5+ years SQL experience, ETL management experience, 2+ years data visualization experience, Scripting for automation experience, AWS technologies experience

Nice to Have

Program management experience, Logistics experience, Operations experience, Supply chain experience, Transportation experience, Translate complex data to business needs, Design measurement frameworks, Design KPI systems, Design analytics strategies, Machine learning experience, Predictive modeling experience, Advanced forecasting experience, Mentoring analysts experience, Mentoring engineers experience, Build self-service BI platforms

What You'll Do.

Own analytics strategy

Design measurement systems

Design business metrics

Empower cross-functional team

Size business opportunities

Prioritize business opportunities

Build analytical models

Apply statistical methods

Conduct deep-dive investigations

Partner with Data Engineering

Improve data accessibility

Drive requirements for data sources

Ensure reliable insights

Write concise documents

Publish data-driven recommendations

How You'll Work.

Team & Collaboration

Cross-functional team; Senior leadership; Centralized Data Engineering

Communication Scope

Present data-driven recommendations; Write concise documents

Full Job Description

Are you excited about using data to shape how millions of products move across the globe? Amazon Global Logistics (GL) is looking for a Sr. Business Intelligence Engineer to own the analytics strategy for our Product & Go-to-Market team. In this role, you'll transform complex international shipping, customs clearance, and freight data into insights that directly influence how we invest, grow, and deliver value to Selling Partners worldwide. Amazon Global Logistics sits at the heart of the Amazon flywheel—by making international shipping more affordable and reliable, we empower Selling Partners to bring more selection to customers, which drives traffic, attracts more sellers, and lowers costs for everyone. Your work will directly measure and accelerate this cycle across the US, EU, UK, and JP marketplaces. You will serve as the subject matter expert on analytics for a cross-functional team of Product Managers, Strategists, Marketers, and Operations Managers. You'll architect scalable analytical models, define measurement frameworks, build self-service dashboards, and present data-driven recommendations to Senior Leadership—turning ambiguity into action at global scale. Key job responsibilities - Own the end-to-end analytics strategy for GL Product & GTM, designing measurement systems, KPIs, and business metrics that guide investment decisions, product roadmaps, and operational performance across ocean freight, air freight, customs clearance, and emerging logistics solutions. - Architect and deliver self-service BI tools (dashboards, reports, automated pipelines) that empower a 12-person cross-functional team and senior leaders to independently access and act on data—reducing time-to-insight and enabling faster decision-making. - Size and prioritize business growth opportunities by building analytical models, applying statistical methods, and conducting deep-dive investigations to maximize return on effort and reduce lead-times from concept to launch. - Partner with c

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