Business Intelligence Analyst, AMZL PSX
Amazon
- Location
- BR, SP, Osasco
- Employment
- Full Time
- Work model
- On-Site
- Level
- Mid
- Posted
- Jun 26, 2026
Skills
About this role
Amazon is the most customer-centric company on Earth. We need exceptionally talented, bright, and driven people who are passionate about doing the right thing. We are looking for a Business Intelligence Analyst to join the Pricing & Payments team within Amazon's Last Mile Brazil organization, as part of the Partner Strategy & Experience (PSX) organization. This role owns the design, development, and maintenance of data intelligence solutions, automated mechanisms, and analytical frameworks that ensure pricing accuracy, payment reliability, and financial health across all delivery partner programs — EDSP (External Delivery Service Provider), AMPL (Amazon Partner Logistics), and AMXL (Amazon Extra Large). As an Individual Contributor, you will be the data and automation backbone of the Payments & Pricing function — building pipelines, dashboards, reconciliation mechanisms, and self-service tools that eliminate manual processes, reduce payment errors, and provide real-time visibility into financial operations. You will partner closely with Payments Specialists, Pricing Specialists, Finance, and Operations to turn complex data into actionable intelligence. This role reports directly to the Pricing & Payments Manager and works cross-functionally with Finance, Operations, Technology, and partner-facing teams. This position is based out of an AMZL office. If you are passionate about building intelligent data solutions, automating complex processes, and driving financial precision through analytics, come join our team. Key job responsibilities Design, build, and maintain automated data pipelines and ETL processes that support payment reconciliation, pricing validation, and financial reporting across all partner programs Develop and maintain SQL-based queries, views, and stored procedures to extract, transform, and analyze large-scale operational and financial datasets Build and maintain dashboards and reporting mechanisms (QuickSight, Tableau, or equivalent) providing real-time visibility into payment status, pricing accuracy, disputes, and financial KPIs Create automated reconciliation mechanisms that identify payment discrepancies, pricing errors, and anomalies before they impact partners — reducing manual intervention and improving trust Develop self-service analytical tools that enable the Payments and Pricing team to access insights without requiring ad-hoc requests Automate recurring reports and manual processes, driving efficiency gains across the Payments & Pricing function Conduct deep-dive analyses on payment cycles, dispute patterns, incentive effectiveness, and pricing model performance to support data-driven decision-making Build alerting and exception-handling mechanisms that proactively flag issues (e.g., payment delays, pricing inconsistencies, unusual dispute volumes) Partner with Technology and Engineering teams to define data requirements, validate data sources, and ensure data quality and integrity Support the development of pricing models and incentive simulations by providing historical data analysis, scenario modeling, and impact projections Document all data solutions, pipelines, and mechanisms with clear technical specifications and operational runbooks Present analytical findings and automation proposals to stakeholders, translating technical solutions into business value A day in the life Your day starts by checking the automated health monitors you built for the payment pipeline. An alert fires — a batch of AMPL partner payments shows a 3% discrepancy against expected values. You dive into the SQL query that powers the reconciliation engine, identify a data source lag from a route restructuring, and push a fix before the payment cycle closes. Mid-morning, you join a sync with the Payments Specialists to review a new automated dispute detection mechanism you're piloting. The early results are promising: 40% of disputes that previously required manual review are now auto-classified and routed, saving