Senior Business Intelligence Engineer, WW FBA Central Analytics

Worldwide Fulfillment by Amazon (WW FBA) empowers millions of sellers to scale globally through Amazon's leading fulfillment network. FBA sellers deliver fast, reliable Prime-eligible shipping and hassle-free returns to customers worldwide—enabling them to focus exclusively on business growth while Amazon handles operational logistics. The WW FBA Central Analytics team architects and maintains data infrastructure that delivers critical insights to WW FBA leadership. This team forms strategic partnerships across global product, program, and technology teams to unify datasets, implement self-service analytics platforms, and develop AI capabilities that transform raw data into actionable insights. We seek a Senior Business Intelligence Engineer to drive data strategy and analytics across multiple high-impact workstreams within our organization. This role operates at the intersection of business intelligence, data platform modernization, and AI-powered analytics. You will own end-to-end BI solutions that transform how stakeholders consume and act on data across the organization. Key job responsibilities - You will design and own unified dimensional frameworks with consistent metric definitions, dimensional cuts, and calculation logic across all reporting surfaces. - You will define metric hierarchies that connect controllable inputs to business outputs, ensuring every metric has a complete definition including formula, data source mapping, calculation logic, data quality rules, and interpretation guidelines. - You will build scalable reporting tables and semantic models that serve multiple downstream use cases (WBR, MBR, dashboards, ad-hoc analysis, GenAI agents) from a single governed source. - You will own end-to-end WBR/MBR reporting infrastructure across WW FBA regions, including automated assembly, validation, and delivery. - You will build and maintain dashboards and self-service analytics solutions that enable PMs to answer business questions without filing a ticket. - You will develop variance decomposition frameworks, root cause analysis templates, and dimensional deep-dive capabilities that support leadership decision-making. - You will translate business questions into analytical approaches, working directly with PMs, Ops, Finance, and Science teams to scope requirements and deliver insights. - You will design and build analytics data models in the lakehouse architecture (Redshift, S3, Spark) optimized for both recurring reporting and ad-hoc exploration. - You will own the semantic layer that connects raw data to business meaning, ensuring consistent definitions across all consumers (dashboards, agents, reports, ad-hoc queries). - You will establish dimensional modeling standards (metric-in-rows format, fully descriptive column names, standardized grain definitions) that support GenAI Text-to-SQL applications. - You will build and maintain validated semantic models that power natural language query agents, ensuring accuracy for business user queries against WBR/MBR data. - You will develop proactive alerting and anomaly detection capabilities that surface issues before they reach leadership review forums. - You will mentor BAs across partner teams on how to leverage the governed analytics infrastructure rather than building independent forks.