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 flywheelby 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 Leadershipturning 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 datareducing 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 centralized Data Engineering teams to improve data assets, quality, and accessibilitydriving requirements for new data sources and ensuring reliable insights from large-scale, multi-source datasets.- Communicate findings and coach peers by writing concise documents, publishing data-driven recommendations to VP-level audiences, and mentoring team members who lead functional strategies on how to leverage data effectively. A day in the life. You might start your morning reviewing dashboard metrics on freight volume and seller adoption, then dive into a deep-dive analysis sizing a new customs clearance opportunity. After lunch, you'll partner with Product Managers to define success metrics for an upcoming launch, followed by presenting quarterly performance insights to GL leadership. About the team. Global Logistics Product & GTM Analytics powers Amazon's international shipping solutionsenabling Selling Partners to move inventory from origins in China, South-East Asia, and beyond into fulfillment centers worldwide. We're a team of builders who combine data engineering, business intelligence, and strategic thinking to accelerate GL's growth. We value curiosity, ownership, and a bias for action. Our work directly fuels the Amazon flywheel by making cross-border logistics simpler and more cost-effectiveso Selling Partners succeed and customers get more selection, faster. Basic Qualifications- 10 years of relevant professional or military experience- 5 years of SQL experience- Experience in ETL management/data pipeline- 2 years of data visualization and reports tools experience- Experience with scripting for automation (e.g., Python) and AWS technologies- Experience applying statistical analysis methods and experimental design to business problems. Preferred Qualifications- Experience in program management, logistics, operations, supply chain, transportation, or a related field- Experience translating between complex data and business needs for non-technical stakeholders, including senior leadership- Experience designing measurement frameworks, KPI systems, or analytics strategies for new business initiatives- Experience with machine learning, predictive modeling, or advanced forecasting applied to operational optimization- Experience mentoring or coaching analysts/engineers on analytical methodologies and best practices- Experience building self-service BI platforms that scale across cross-functional teams.