BI Engineer, AWS Finance, Analytics and Science Team

$89,600 - $185,000/Yr

Amazon - Seattle, WA

Full-time - Mid Level

Seattle, WA

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

About the position

AWS is one of Amazon's largest and fastest growing businesses, serving millions of customers in more than 190 countries. We use cloud computing to reshape the way global enterprises use information technology. We are looking for entrepreneurial, analytical, creative, flexible leaders to help us redefine the information technology industry. If you want to join a fast-paced, innovative team that is making history, this is the place for you. The AWS Finance Analytics and Science Team (FAST) is responsible for many of the key functions needed by the AWS global sales organization, including building and operating the data resources that provide the AWS sales organization with insights into all areas of business performance. The successful candidate will be an expert with SQL, ETL (and general data wrangling), and have exemplary communication skills. The candidate will need to be comfortable with ambiguity in a fast-paced and ever-changing environment, and able to think big while paying careful attention to detail. The candidate will know and love working with business intelligence tools and can partner with customers to answer key business questions.

Responsibilities

• Work with business customers to gather requirements and deliver complete data analytical solutions
• Learn why customers are asking for data and what their underlying questions and business goals are
• Own the design, development, and maintenance of ongoing metrics and analyses used to drive key business decisions
• Recognize and adopt best practices, including data integrity, accuracy, and reliability, as well as documentation
• Drive data democratization throughout the organization, enabling others to self-serve their data needs

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

• Full range of medical benefits
• Financial benefits including equity and sign-on payments
• Comprehensive employee benefits package