Senior BI Engineer: AI-Driven Analytics Platform Architect

Amazon; Seattle (WA); On-site; USD 130,000 - 176,000; Full time

Job summary

Amazon is seeking a Senior Business Intelligence Engineer III to lead analytics strategy for the Specialist Insights team, focusing on Data and AI. The role blends data engineering with AI, building systems where automation handles routine tasks while humans address exceptions and strategy.

The ideal candidate will own end-to-end analytics architecture, set technical standards, and drive evolution from traditional reporting to AI-enabled, scalable solutions at scale.

Qualifications

• 7+ years as a Data Analyst, Data Engineer, BI Analyst, or related role.
• Experience building end-to-end data platforms and analytics solutions.
• Strong SQL and Python scripting abilities with production-scale systems.

Responsibilities

• Owns analytics architecture for data platforms, governance, and AI-integrated patterns.
• Designs scalable data platforms, pipelines, quality monitoring, and schema management.
• Architects governance frameworks for data trust at scale with AI considerations.
• Builds automated analytics systems for reporting, KPI monitoring, and insights.
• Defines tooling strategy and shared infrastructure for AI/ML capabilities.
• Leads cross-functional alignment on data product architecture and APIs.
• Makes high-impact technical decisions affecting the data stack.
• Applies ML/AI methods in production and designs experiments to quantify impact.
• Mentors the team in data engineering, system design, and AI applications.
• Communicates architecture and strategy to leadership with clear trade-offs.

Skills

Data Analysis

Data Engineering

SQL

Python

Automation Scripting

Education

Bachelor's degree

Tools

SQL

Python

Job description

Amazon is seeking a Senior Business Intelligence Engineer III to lead analytics strategy for the Specialist Insights team, focusing on Data and AI. The role blends data engineering with AI, building systems where automation handles routine tasks while humans address exceptions and strategy.

The ideal candidate will own end-to-end analytics architecture, set technical standards, and drive evolution from traditional reporting to AI-enabled, scalable solutions at scale.