Business Intelligence Engineer, FCGT

The International Seller Services Analytics team for WW Reimbursements is looking for a Senior Business Intelligence Engineer to lead advanced analytics for our Product and Business teams. You'll bring together large, multi-dimensional datasets across reimbursement claims, inventory discrepancies, and seller settlements to build data models and insights that drive high-impact decisions. As part of the International Seller Services Analytics team, you'll partner with business, finance, and engineering stakeholders to turn complex data into actions that protect seller trust and Amazon's financial accuracy. If you're customer obsessed, hands-on with SQL and Python, and energized by solving ambiguous problems at scale, this role is for you.

Key job responsibilities
The International Seller Services Analytics team for Amazon's Worldwide (WW) Reimbursements organization is seeking a talented, self-driven and experienced Senior Business Intelligence Engineer to lead the advanced analytics wing for the WW Reimbursements Product and Business team. This pivotal role gives you the opportunity to work with an exceptionally innovative team, slice and dice multi-dimensional, high-depth data across reimbursement claims, inventory discrepancies, and seller settlements, and build complex data models that drive data-driven insights for high-impact decisions spanning Seller and Customer experience, financial accuracy, and loss-prevention Product/Program initiatives.

Are you customer obsessed, flexible, smart and analytical, strategic yet execution focused, and passionate about e-commerce and operational excellence? Are you an experienced, entrepreneurial leader with a strong work ethic? If yes, this opportunity will appeal to you.

To be successful in this role, you will have the ability to roll up your sleeves, innovate, and quickly become a subject matter expert on the reimbursement lifecycle, assessing performance across claim types, fulfillment channels, and marketplaces. You will be a self-starter who is willing to work hands-on, is comfortable with ambiguity and large data sets. You will be part of the International Seller Services Analytics team working with Stakeholders, Finance partners, Data Engineers, Business Intelligence Engineers and Business Analysts to achieve our goals. You will also have strong communication skills, be able to work closely with stakeholders, and translate data-driven findings into actionable insights that protect both seller trust and Amazon's financial integrity.

You will have demonstrated proficiency in SQL across a variety of databases, BI tools, and R or Python to analyze large data sets.

Key job responsibilities

Passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions.
You should have deep expertise in the creation and management of datasets, with exposure to implementing and operating stable, scalable data flow solutions from production systems into end-user-facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive.
Detail-oriented with an aptitude for solving unstructured problems, especially where reimbursement discrepancies, root-cause attribution, and financial reconciliation demand precision. You should work in a self-directed environment, own tasks and drive them to completion.
Excellent business and communication skills to work with business and finance owners to develop and define key business questions, and to build data sets that answer those questions across the WW Reimbursements space.

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 2+ years of Tableau Desktop, Quicksight or other relevant data visualization software experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field

- Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business

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