Business Intelligence Engineer, AWS Field Exp - BPO

Amazon; Dallas (TX); On-site; USD 110,000 - 140,000; Full time

Job summary

Amazon is seeking a Business Intelligence Engineer to own the measurement and analytics layer for agentic AI automation across AWS BPO operations. You will design, build, and maintain data pipelines, ETL/ELT processes, and BI reporting that quantify automation impact and inform leadership decisions.

This role blends data engineering, BI, and AI operations, requiring a technical platform mindset, reliability, and ability to deliver actionable insights in a fast-moving environment.

Qualifications

• Experience building data pipelines and analytics platforms.
• Strong knowledge of BI design, metrics, and dashboards.
• Experience with ETL/ELT processes and data quality.

Responsibilities

• Design, implement, and deliver BI solutions that measure automation impact.
• Define key metrics to evaluate automation effectiveness.
• Analyze problems and understand how AI-driven workflows interact with human operations.
• Build and maintain data pipelines and scheduling/orchestration systems.
• Produce insights and recommendations for leadership.
• Support internal customers with dashboards and self-service analytics.

Skills

Data engineering

Business intelligence

ETL/ELT

Analytics

Observability

Tools

Redshift

AWS Glue

Airflow

Job description

Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform, offering over 100 fully featured services to millions of active customers globally, including the fastest-growing startups, largest enterprises, and leading government agencies.

Business Product & Operations (BPO), part of the AWS Field Experience (AFX) organization, builds the data infrastructure and automation systems that power Sales, Marketing, and Global Services (SMGS) Operations. The team owns analytics platforms, data pipelines, and measurement frameworks that enable operational teams to quantify automation impact and make data-driven decisions at scale.

We are looking for a Business Intelligence Engineer who will own the measurement and analytics layer for agentic AI automation across BPO operations. This role sits at the intersection of data engineering, business intelligence, and AI operations. You will quantify the impact of AI-driven automation on operational workflows, build and maintain the data pipelines that feed reporting and decision-making, and partner directly with internal customers to deliver actionable insights.

This is not a traditional BI role. The right candidate leans toward technical platform work: building reliable data pipelines, managing scheduling infrastructure, troubleshooting ETL failures, and improving data quality at the source. You will operate in a fast-moving environment where automation capabilities evolve weekly and measurement frameworks must keep pace.

Key job responsibilities

• Design, implement, and deliver BI solutions that measure the impact of agentic AI automation on operational efficiency, accuracy, and throughput
• Identify opportunities and define key metrics to evaluate automation effectiveness and drive business strategy
• Analyze and solve problems at their root, stepping back to understand the broader context of how AI-driven workflows interact with human operations
• Build and maintain data pipelines (ETL/ELT), scheduling infrastructure, and orchestration systems that power downstream analytics and reporting
• Conduct deep-dive analyses of automation performance, formulate conclusions, and present recommendations to leadership
• Produce written insights for stakeholders that shape metric development, automation investment decisions, and operational reporting
• Simplify and automate reporting, audits, and other data-driven activities, leveraging AI tooling where applicable
• Partner with Data Engineering and platform teams to enhance data infrastructure, data availability, and broad access to automation and customer insights
• Develop and drive best practices in data integrity, pipeline reliability, validation, and documentation
• Instrument AI automation systems for measurable outcomes, working with engineering teams to close observability gaps
• Support internal customers across SMGS Operations with analytics solutions (dashboards, ad-hoc analyses, self-service tools)
• Learn and adopt new technologies and techniques to meaningfully support product and process innovation in AI-driven operations

A day in the life

• Measuring agentic AI automation outcomes: throughput, accuracy, cycle time reduction, and customer impact across BPO operations
• Owning and operating data pipelines in Redshift/Glue/Airflow that feed executive dashboards and operational reporting
• Supporting internal customers (operations managers, program leads) with ad-hoc analysis and self-service analytics
• Pipeline scheduling, monitoring, and incident response (data freshness SLAs)
• Working directly with the Sprinters SDE team to instrument new automation features for observability

About the team

About AWS

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

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