Business Intelligence Engineer II, Security Assurance Engineering

- 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
- 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

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $89,600/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
At AWS, Security is priority zero. As part of the Amazon Web Services (AWS) Security team, we are looking for a creative problem solver, analytical and technically skilled Business Intelligence Engineer to join our team.

As a part of AWS Security, you’ll get to operate in a constantly changing environment and get to work with AWS business and engineering teams on business-critical security projects and programs. We work across AWS to drive strategic security initiatives, design, and deliver tooling and automation, and continue to raise the bar on security at AWS.

As a Business Intelligence Engineer, you'll be instrumental in constructing data pipelines, crafting robust metrics, and conducting advanced statistical analyses to gauge the effectiveness of our security programs. Your role will encompass leading end-to-end development of business intelligence solutions, empowering strategic decision-making processes. If you excel at distilling complex data insights into actionable strategies and can effectively communicate them to both technical and non-technical stakeholders, we'd love to hear from you.



Key job responsibilities
Key job responsibilities

* Contribute to the design, implementation, and delivery of BI solutions for complex and ambiguous problems.
* Produce recommendations and insights for key stakeholders that will help shape effective metric development and reporting.
* Design, develop and maintain scaled, automated, user-friendly systems, reports, dashboards, etc. that will support the needs of the business.
* Apply deep analytic and business intelligence skills to extract meaningful insights and learning from large and complicated data sets.
* Simplify and automate reporting, audits, and other data-driven activities.
* Partner with Engineering to enhance data infrastructure, data availability, and broad access to customer insights.
* Use data mining, model building, and other analytical techniques to develop and maintain customer segmentation and predictive models to drive the business.
* Analyze and solve problems at their root, stepping back to understand the broader context.
* Develop and drive best practices in data integrity, consistency, analysis, validations, and documentation.