Senior Business Intelligence Engineer, WW FBA Central Analytics

Amazon.com Services LLC•4h ago

United StatesOnsite$130.4K–$176.3KFull-timeSenior Level10+ yrs exp

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Analytics EngineerBusiness AnalystHr Business Partner

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
technology teams to unify datasets, implement self-service analytics platforms
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
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
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
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
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
dimensional deep-dive capabilities that support leadership decision-making. - You will translate business questions into analytical approaches, working directly with PMs, Ops, Finance
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.
10+ years of professional or military experience - 5+ years of SQL experience - 1+ years of SQL, ETL or Oracle experience - 1+ years of processing large, multi-dimensional datasets from multiple sources experience - 1+ years of performing statistical analysis experience - 1+ years of developing automated reporting experience - 5+ years of as a Data Analyst, Data Engineer, Business Intelligence Analyst
a related occupation experience - 1+ years of using SQL, ETL (Extract, Transform, Load)
Oracle experience - Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics
a related field - Experience programming to extract, transform and clean large (multi-TB) data sets - Experience with theory and practice of design of experiments and statistical analysis of results - Experience with AWS technologies - Experience in scripting for automation (e.g. Python) and advanced SQL skills. - Experience with theory and practice of information retrieval, data science, machine learning and data mining
Experience working directly with business stakeholders to translate between data and business needs - Experience managing, analyzing and communicating results to senior leadership Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability
other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications
location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off
parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, WA, Seattle - 130,400.00 - 176,300.00 USD annually

Required skills

SQLETLOraclePythonAWSData AnalysisData EngineeringBusiness IntelligenceStatistical AnalysisData ScienceMachine LearningData Mining