The Amazon Security Experiences (ASE) organization is the data intelligence backbone of Amazon Security. We build and operate the data platform that powers security insights, builder experience analytics, and tooling decisions across Amazon's security ecosystem. Every insight surfaced to security leadership, from builder productivity trends to security issue quality metrics, flows through systems our team designs, builds, and maintains.
We operate at scale, processing large volumes of security and operational data daily through hundreds of pipelines consisting of transformations, reporting queries, ingestions, and infrastructure management scripts. Our engineers work directly with source systems across AWS and SDO (Security, Developer, and Operations) data domains to procure data, convert it into structured formats, build large-scale processing pipelines, design analytical data models, and maintain infrastructure with the highest security and compliance standards.
We are seeking a Business Intelligence Engineer I to join our Security Data Intelligence (SDI) team. In this role, you will build and maintain BI solutions (datasets, queries, reports, dashboards, and analyses) that inform how security leadership makes decisions across Amazon. Working on well-defined problems with guidance from senior engineers, you will maintain data lineage understanding, apply analytics and visualization tools, and deliver reliable insights on schedule. You will partner with teams across ASE, BizOps, MapSec, and other security organizations to translate business questions into data-driven answers that serve the broader Amazon Security organization.
Key job responsibilities
Learn and apply team BI best practices when building data artifacts including ETL, data models, queries, and reports. Measure and improve dataset quality across owned solutions. Automate manual processes where possible.
Maintain understanding of relevant data lineage: sources of data, how metrics are aggregated, and how BI is consumed and acted upon by security leadership. Learn the business context behind the team's data infrastructure and metrics definitions. Investigate data anomalies and validate outputs against source data and business logic.
Build small to mid-size BI solutions, or components of larger solutions, to answer straightforward business questions with data. Be proficient in SQL, maintain straightforward ETL, and create data structures using schema definition languages. Use analytics and visualization tools (e.g., QuickSight, Excel, Tableau) to deliver actionable insights.
Write secure, stable, testable, and maintainable code with minimal defects. Get analyses and code reviewed before deployment. Document solutions for ease of use, interpretation, and maintainability. Handle data in accordance with Amazon security and compliance policies.
Solve straightforward problems where what to accomplish is clear but how requires skill a