Business Intelligence Engineer, AWS Field Exp - BPO

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.

Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

About Sales, Marketing and Global Services (SMGS)

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.

Basic Qualifications

- 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 using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field

Preferred Qualifications

- 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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, TX, Dallas - 99,500.00 - 160,000.00 USD annually
USA, WA, Seattle - 99,500.00 - 160,000.00 USD annually