Global BI Engineer for Defect-Elimination Analytics

Amazon; Austin (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Amazon is seeking a Business Intelligence Engineer to surface insights, define KPIs, and build robust measurement systems that guide defect elimination at scale in the Austin area. You will partner with software developers, product managers, economists, and ML teams to surface insights and track progress against goals.

The role emphasizes designing scalable dashboards, data architectures, and automated pipelines, enabling self-serve analytics and AI-driven automation of routine analytics tasks.

Qualifications

• Experience designing dashboards and KPI reporting.
• Ability to translate business questions into analytics and actionable insights.
• Collaborating with cross-functional teams including software, PMs and econ teams.
• Familiarity with AI/ML data workflows and data infrastructure.

Responsibilities

• Design, develop and maintain scaled, automated dashboards and reports.
• Define and implement KPIs and reporting solutions with cross-functional teams.
• Design data architectures enabling self-serve analytics for AI agents.
• Automate end-to-end data pipelines for applications and ML models.
• Extract insights from large, complex datasets including unstructured text for generative AI.
• Collaborate between business and technical teams to drive project objectives.
• Leverage LLM-based agents to automate analytics tasks (queries, validation, anomalies, narration).
• Stay current on AI/ML data infrastructure and evaluate applicability to defects elimination use cases.

Skills

Dashboard design

KPI development

Data infrastructure

LLM/AI applications

Data storytelling

Tools

SQL

Python

ETL tools

Job description

Amazon is seeking a Business Intelligence Engineer to surface insights, define KPIs, and build robust measurement systems that guide defect elimination at scale in the Austin area. You will partner with software developers, product managers, economists, and ML teams to surface insights and track progress against goals.

The role emphasizes designing scalable dashboards, data architectures, and automated pipelines, enabling self-serve analytics and AI-driven automation of routine analytics tasks.