Business Intelligence Engineer, Amazon Global Logistics

Amazon has spent years building one of the world’s most efficient and optimized supply chains. Amazon Global Logistics (AGL) builds on that foundation with innovative distribution and end-to-end supply chain service for FBA sellers.

As a Business Intelligence Engineer at Amazon Global Logistics (AGL), you will be the strategic insights provider driving the business adoption for a 30+ AGL shipping/storage product and solution portfolio for APAC sellers across multiple origins to marketplaces.
You are responsible for identifying the growth opportunity and alerting risks with inputs from sales/product and GTM teams, data mining into actionable business GTM planning and campaigns, market competitiveness analysis and product feature rampup request validations proofs.
Your mission is to scale AGL’s market adoption target through data-driven hypotheses, rigorous ROI governance, and the automation of growth workflows.

Key job responsibilities
- Design, develop, and maintain scalable data infrastructure and ETL pipelines to support business intelligence initiatives using automated dashboard solutions
- Partner with Product, Technical, Business, and Marketing teams to understand data requirements and design scalable and user-friendly BI solutions
- Design and implement AI/LLM-powered solutions to automate human-in-the-loop tasks
- Design and develop statistical analysis to support business decision making using the AI infrastructure and company wide solutions

Basic Qualifications:
- 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
- Bachelor's degree or above in business administration, finance, economics, computer science, data science, engineering, or other related field, or 2+ years of Amazon RME (BB/3P) Full Time Exempt experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience using SQL (Structured Query Language) to pull data from a database or data warehouse
- Experience using Python scripting to process data for modeling

Preferred Qualifications:
- Master's degree or above in BI, finance, engineering, statistics, computer science, mathematics or equivalent quantitative field
- Knowledge of Microsoft Excel at an advanced level, including: pivot tables, macros, index/match, vlookup, VBA, data links, etc.
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
- Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business

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