Business Intelligence Engineer II, Application Security, Stores Security

About the position

Amazon seeks an experienced Business Intelligence Engineer (BIE) to join the Application Security Data Operations and Engineering Team. Our mission is to prevent software weaknesses from making it into production. We interact with Amazon businesses, including AWS, customers, vendors, sellers, subsidiaries etc. We build automatic mechanisms to detect and prevent prohibit software vulnerabilities and weaknesses from being released to customers. Our global organization uses a diverse set of algorithms and machine learning techniques. We screen over half a billion events every day, integrate with Tier 1 systems and deal with unique scaling challenges. We are still Day 1 and have an exciting road map to build Machine Learning (ML) and Analytics powered detection and resolution systems to help scale Amazon for years to come. In this role you'll own everything from ad-hoc reporting to long term analytical and statistical projects that will affect the effectiveness of the Application Security team and complementary programs. You'll work with multiple Amazon Businesses and Functions, work with multiple data sources and a wide range of data technologies (e.g. Redshift, S3, Tableau, Quicksight etc.), stay abreast of emerging technologies, investigate and implement where appropriate.

Responsibilities

• Interface with business customers to gather requirements, drive reporting or analytic projects to help solve complex challenges.
• Design, implement, and support datasets that provide structured data for reporting and analysis.
• Develop reports and dashboards across various business teams to drive adoption and increase visibility into key measures of business performance.
• Analyze billions of rows of data to find the root causes behind variances and drive business insights.
• Investigate and implement new big data technologies to provide automatic resolutions to address business 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

• Flexible work hours and arrangements
• Endless knowledge-sharing, training, and other career-advancing resources
• Work-life harmony