
Business Intelligence Engineer III, Emerging Marketplaces Analytics
Last Date to Apply: July 29, 2025
ApplyAdded Today : 1429
Expired Today : 35
Amazon
Emerging Marketplaces Analytics team builds Analytics solutions that drive customer growth across all EMs for Amazon. These solutions include building and scaling complex analytical frameworks, mining data-driven insights through comprehensive dashboards, using ML/AI to address business problems, and leading Analytics for key strategic review meetings with leadership.
Key job responsibilities
Key job responsibilities
- Conduct deep dive analyses of business problem statements and formulate conclusions and recommendations to leadership
- Share written recommendations and insights for key stakeholders that will help shape organizational strategic decisions and priorities
- Contribute to the design, implementation, and delivery of BI solutions for complex and ambiguous problems
- Simplify and automate reporting, audits and other data-driven activities
- Partner with other BIEs to enhance data infrastructure, data availability, and broad access to customer insights
- Develop and drive best practices in data integrity, consistency, analysis, validations, and documentation
- Learn new technology and techniques to meaningfully support internal stakeholders and process innovation
About the team
We are the Emerging Prime, Lifecycle and XCM (PLX) EMXO team that builds & orchestrates inputs towards Customer Growth and Engagement for our Stores across ten locales. We do this through: (i) Crafting EM-specific frameworks where none exist to guide inputs, prioritization and investment decisions; (ii) Building foundational tech, tools & capabilities to enable inputs at scale, sharper targeting of key customer cohorts, driving down Cost-To-Serve (CTS) through core builds; and (iii) Orchestrating EM-focused builds by influencing partner WW teams and x-EM experiments across the customer Lifecycle - 8+ years of professional or military experience
- 6+ years of SQL experience
- 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 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
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