Senior Business Intelligence Engineer - Information Security

• BA/BS degree in Computer Science, Mathematics, Information Systems or related field and 5+ years of industry experience, or equivalent combination of degree and experience
• Advanced SQL querying
• Advanced expertise in Excel
• Experience with data visualization tools such as Tableau, QuickSight, MicroStrategy or similar tools
• Experience working with large-scale, complex datasets
• Demonstrated strength in data modeling, ETL development, and Data warehousing.
• Strong verbal/written communication & data presentation skills, including an ability to effectively develop and communicate clear, thoughtful, and comprehensive analyses.

At Amazon, we are obsessed with customer trust. Information Security enables Amazon business leaders to securely develop and operate to maintain Customer Trust by guarding the confidentiality and integrity of Amazon and customer data.

Our teams span over ten countries worldwide, and our focus areas include security intelligence, application security, incident response, security operations, risk and compliance, acquisitions and subsidiaries, and external partner security. Our mission includes instilling awareness to safeguard all customer and employee data, applications, services, and assets. To accomplish this, we unite with Amazon organizations to build security best practices into enterprise-wide systems. Our guidance and leadership equip our partners to maintain high-security standards. This team dives deep into security technologies and continuously raises the security bar across Amazon’s Consumer, Digital and Other (CDO) by tackling complex engineering problems that require widespread support and multi-year execution plans.

We are looking for a Senior Business Intelligence Engineer with broad technical skills to design and build analytic reporting capabilities to deliver on strategic security projects, define/produce end-to-end metrics that enable security and business decisions. As the team’s Senior Business Intelligence Engineer, you will develop Data Visualizations and Self-Services tools in AWS QuickSight, Write SQL to Extract and Transform Data from Databases by analyzing the data to find patterns and understand relationships.

You will drive best practices and set standards for our team on reporting, data visualization by combining varied best practices across decentralized, global teams. BUT you have an opportunity to build products that impact across all of Amazon. You will solve complex analytical problems that will affect all of Amazon’s CDO organization, including a variety of large and growing businesses. It includes the Consumer Web site, the fulfilment centers, TV and Movie Studios, Prime Video, Devices (Alexa, Kindle, FireTV), IMDB, Zappos, Whole Foods and many other businesses. It will provide opportunities to think big, be customer obsessed, and partner with business teams across Amazon.com. We dive deep into security technologies such as new identity and authentication systems, hardware security components, cryptography, system hardening, and massive-scale audit analysis. This program aims to define the innovative preventative, detective, and monitoring mechanisms to enable security at scale. You will discover, define, and solve challenging problems across multiple teams and locations in this role.

This position may be located in Austin TX or Arlington VA, Relocation available.

Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.

• Master’s degree in Computer Science, Mathematics, Information Systems or related field and 5+ years industry experience
• Experience with programming tools (Python, R, etc.) to create custom applications based upon analytical needs.
• Familiar with Redshift, Hadoop, Java Technical proficiency in programs such as R, SAS, SPSS or Stata
• Proficiency with at least one statistical software package (e.g. R, SPSS)
• Proven capability in statistical analysis (e.g., ability to conduct analyses using regression, modeling, forecasting approaches, and related tools)
• Experience with Machine Learning Techniques to Understand Data Patterns and Make Predictions