Join the Risk and Compliance Solutions (RCS) team at Amazon and play a pivotal role in safeguarding the world's largest store. This role is for a Business Intelligence Engineer (BIE) who will develop data systems that empower Amazon's compliance operations, blending technical expertise with business insight to transform complex data into actionable intelligence.

This position involves working with a variety of data technologies, including Amazon Redshift, AWS Lambda, and Amazon QuickSight. You will contribute to crucial data modeling and design decisions, and stay abreast of emerging technologies, with opportunities to leverage AI for automating reporting processes and pipelines.

The ideal candidate is a data enthusiast with strong analytical skills, a proactive approach to ambiguity, meticulous attention to detail, and a drive to succeed in a dynamic, entrepreneurial environment.

Design, build, and maintain scalable, automated, and user-friendly datasets, reports, and dashboards to meet analytical and business needs. Write complex SQL queries for ad-hoc requests, in-depth analyses, and routine reporting. Implement and support essential datasets to provide stakeholders with structured and timely access to actionable business information. Gather requirements directly from stakeholders and take ownership of automated end-to-end reporting solutions. Collaborate with analysts, data engineers, and software development engineers across RCS and Amazon to deliver comprehensive data solutions. Streamline and automate reporting, audits, and other data-driven activities, creating solutions for scale and enabling stakeholder self-service. Contribute to AI-driven solutions aimed at automating manual processes and pipelines, thereby enhancing organizational operational efficiency. Develop a deep understanding of Amazon's diverse data resources and know how, when, and what to utilize effectively.

Possess at least two years of experience in analyzing and interpreting data, with a background in technologies like Redshift, Oracle, or NoSQL. Demonstrate experience with data visualization tools such as Tableau, Quicksight, or similar platforms. Proficient in using industry analytics visualization tools (e.g., Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g., t-test, Chi-squared). Experience with at least one scripting language, including Python, Java, or R, is required.

A Master's degree or an advanced technical degree is preferred. Familiarity with data modeling and data pipeline design is advantageous. Experience with statistical analysis and correlation analysis is a plus.