Business Intelligence Engineer
Amazon
About the Role
At Amazon, we are building a procurement organization powered by trusted, scalable, and AI-ready data. The Global Procurement Organization (GPO) is seeking a Business Intelligence Engineer to support the Central Services pillar (GPCS), driving sourcing visibility, compliance analytics, and vendor performance insights across global procurement. This role sits within the BI&A team under Global Procurement Technology (GPT) and focuses on transforming fragmented operational data into standardized, governed analytical products. You will work on high-impact initiatives such as sourcing analytics, compliance monitoring, and vendor management reporting, while contributing to the GPO Data Hub—our foundation for scalable self-service and AI-enabled decision making. This is a hands-on role for someone who can partner with business stakeholders, build robust data models, and deliver clear, actionable insights in a fast-paced environment.
Key Responsibilities
- Own and deliver BI solutions (datasets, dashboards, and analyses) supporting sourcing, compliance, and vendor management programs
- Contribute to the development of governed, reusable data products aligned with the GPO Data Hub
- Partner with business stakeholders to define metrics, translate requirements, and drive adoption of standardized reporting
- Build and maintain scalable data models and ETL pipelines using SQL and Python on AWS
- Ensure data quality, consistency, and documentation across analytical outputs
- Develop intuitive visualizations that enable clear decision-making for procurement leaders
- Collaborate with cross-functional teams within GPT and BI&A to align on data definitions, architecture, and best practices
Requirements & Tech Stack
- SQL
- Python
- AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Tableau, Quicksight, or similar data visualization tools
Qualifications
- Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
- Experience with data modeling, warehousing, and building ETL pipelines
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Master's degree in sciences, engineering, finance or equivalent
Preferred Qualifications
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience with forecasting and statistical analysis