Business Intelligence Engineer, GFP Analytics (GFPA)

$89,600 - $185,000/Yr

Amazon - Bellevue, WA

Full-time - Mid Level

Bellevue, WA

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Business Intelligence Engineer (BIE) role within the Global Fleet and Products Analytics (GFPA) team at Amazon focuses on leveraging data to support strategic initiatives in the Last Mile space. The BIE will develop technical solutions, influence decision-making, and manage complex projects that drive operational excellence and efficiency in package delivery. This position requires strong communication and problem-solving skills, as well as the ability to work with ambiguity and large datasets.

Responsibilities

• Provide strategic advisory to business teams and leaders that liaise technical and business needs.
• Engineer critical input and output metrics.
• Create performance metrics to measure operational performance, identify root causes and trends, and prescribe action plans for delivery stations around the globe.
• Manage metrics across multiple projects simultaneously.
• Work with product, technology, and analytics teams to support the development of tools and dashboards.
• Communicate with and support various internal stakeholders and external audiences.
• Learn, explore, apply, and gain expertise in many internal Amazon data and public AWS products including Glue, Redshift, Quicksight, and Lambda.

Requirements

• 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. 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.

Nice-to-haves

• 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.

Benefits

• Medical insurance
• Financial benefits
• Equity options
• Sign-on payments
• Comprehensive employee benefits package