Are you customer obsessed, flexible, smart and analytical, strategic yet execution focused, hungry and passionate about e-commerce, experienced, and with a strong work ethic? If yes, this opportunity will appeal to you.
We are building the future of data-driven decision making. In this role, you will be at the forefront of creating single sources of truth and data infrastructure that will power agentic AI solutions — enabling self-service intelligence, reducing dependency on traditional BI workflows, and unlocking the next generation of automated, agent-driven insights across the business.
The ideal candidate will be enthusiastic about managing challenging, lengthy projects across multiple teams. We are looking for a Business Analyst who shares Amazon's passion for the customer—someone who understands both Engineering and Business. This role requires an individual with excellent understanding of SQL, building ETL pipelines, query development, and designing scalable data architectures that serve as foundational layers for AI and machine learning systems. You should have good business acumen and the ability to work with business, program, and product teams. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment, and driven by a desire to innovate in this space.
To be successful in this role you should have superior communication, presentation, and organizational skills. Operating in a fast-moving and sometimes ambiguous environment, you will work autonomously taking control and responsibility for achieving the objectives of the role. This role provides opportunities to develop original ideas, approaches, and solutions in a competitive and ever-changing business climate.
You will partner with product management teams to identify long-term features and programs to improve the seller and customer experience on the Amazon platform. Additionally, you will collaborate with AI/ML and engineering teams to ensure data pipelines, schemas, and governance frameworks are optimized for agentic AI consumption — building trusted, well-documented, and semantically rich datasets that empower intelligent agents to deliver accurate, real-time insights at scale.
Key job responsibilities Develop a deep understanding of Amazon Seller Services products and services; design and maintain single sources of truth that track and report business performance and problem areas using well-defined, trusted metrics Work cross-functionally with the account management team to identify and fix problems with sellers, leveraging data-driven insights and AI-ready datasets that enable faster root-cause analysis Use Amazon's tools — including emerging AI and agentic solutions — to problem solve, validate solutions, and build scalable, repeatable analytical frameworks that reduce manual intervention Partner with stakeholders to define goals around key operational metrics, ensuring metric definitions are semantically rich, well-documented, and structured for consumption by AI agents and LLM-powered systems Recommend business actions based on analytical findings; this includes defining new metrics, techniques, and strategies to improve seller performance — with a focus on enabling self-service access and powering agentic AI workflows that can autonomously surface insights and trigger actions Architect and maintain AI-ready data infrastructure — including clean data pipelines, standardized schemas, data contracts, and lineage tracking — that serves as the foundation for agentic AI solutions across the organization Champion data quality and governance by establishing frameworks that ensure AI-powered solutions deliver reliable, trustworthy, and explainable outputs at scale
Basic Qualifications
- 1+ years of data analytics or automation experience
- 1+ years of capacity planning, operations planning, business analysis or similar experience
- Bachelor's degree
- Knowledge of data pipelining and extraction using SQL
- Knowledge of SQL and Excel at a moderate or advanced level
- Experience with data mining tools like SQL, SAS, SPSS, or similar
Preferred Qualifications
- Knowledge of SQL/Python/R, scripting, MS Excel, table joins, and aggregate analytical functions
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