Business Intelligence Engineer II, Rapid and Rural Logistics, R2L

The Rapid & Rural Logistics (R2L) team at Amazon is seeking a Business Intelligence (BI) Engineer to join their Automation Team. This role is part of a high-growth portfolio managing rush service and super rural delivery operations including Sub Same Day (SSD), Rural Super Rural (RSR), and Amazon Today services.

As a BI Engineer, you'll focus on process automation, operational insight, and analytical support for these delivery businesses. The position requires advanced analytical and problem-solving skills, with a strong emphasis on building automated solutions for operational management. You'll work closely with Delivery and operations teams to streamline Program Manager manual processes.

The ideal candidate should be proficient in data visualization tools like QuickSight and Tableau, possess strong data modeling skills, and have experience with ETL processes, SQL, and scripting. You'll be responsible for designing and developing projects that drive key business decisions, building innovative data solutions with large-scale systems, and creating deep-dive tools and dashboards to communicate insights.

This role offers an exciting opportunity to impact Amazon's delivery operations through technology-driven solutions. You'll work in a fast-paced environment that values creativity, autonomy, and a strong bias for action. The position comes with competitive compensation ranging from $89,600 to $185,000 based on location and experience, plus comprehensive benefits and potential equity compensation.

The role requires excellent communication skills and the ability to collaborate effectively with business stakeholders and cross-functional teams. You'll be expected to balance technical expertise with strong business acumen, working independently while maintaining alignment with team goals. This is an excellent opportunity for a data professional who wants to make a significant impact on Amazon's logistics operations while working with cutting-edge technologies and large-scale systems.