Business Intelligence Engineer, Vulnerability Management and Remediation

Amazon
USA, TX, Austin2025-12-01ONSITE

About the job

Do you get excited about working with hyper scale data applications? Interested in security? Enjoy working with the latest and greatest AWS technologies? Ready to pioneer our data analysis, dashboarding, and storage solutions for a pipeline managing petabytes of data to transform the efficiency of our systems and customers? Here in Defensive Security, we have that special role just for you! The Vulnerability Management and Remediation team is building the next generation of mission critical data processing pipelines and applications. Our innovations handle petabyte scale data, in real time. These applications enable Amazon defensive security and security management teams globally. Our customers are Amazon, internal stakeholders, and Amazon’s customers. Our engineers work directly with stakeholders, get close to customers' needs, and are empowered to take technical risks to build the best-in-class software with respect to quality, scale, and insights. The technical foundation this team builds, helps keep all of Amazon (Fulfillment Centers, Physical Stores, Whole Foods, Fresh, etc.) secure.

Responsibilities

Design, develop, and maintain scalable data infrastructure and ETL pipelines to support business intelligence initiatives using automated dashboard solutions

Partner with Technical, Business, Operation, and Security teams to understand data requirements and design scalable and user-friendly BI solutions

Design and implement AI/LLM-powered solutions to automate human-in-the-loop tasks

Design and develop statistical analysis to support business decision making using the AI infrastructure and company wide solutions

Manage and execute entire project from start to finish including problem solving, data gathering and manipulation, predictive modeling and project management

Qualifications

Minimum

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

Preferred

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