AMAZON Senior Business Intelligence Engineer, Devices Demand Science Optimization in Seattle, WA

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Description

We're looking for a Senior Business Intelligence Engineer (BIE) to build AI-powered data products for Amazon Devices. You'll design and maintain MCP servers and semantic layers that make our core tables accessible to AI agents, automate daily business workflows (WBR narratives, flashes, executive summaries) using GenAI, and architect scalable data pipelines on AWS.

This role sits at the intersection of analytics, data engineering, AI, and product development you'll define how machines understand our business data and scale that intelligence across multiple BI teams.

Key job responsibilities
- Design, build, and maintain scalable core data tables and pipelines that serve as the single source of truth for Devices sales, inventory, pricing and demand planning metrics.
- Automate reporting workflows and data processes to reduce manual effort and improve speed, accuracy, and reliability of insights delivered to stakeholders.
- Build and enhance QuickSuite dashboards that provide self service analytics for product line leaders, finance, and supply chain teams.
- Develop contextual data layers that connect disparate data sources into unified, business ready datasets, enabling deeper analysis and cross functional visibility.
- Build and integrate AI powered features into BI solutions, including intelligent agents, automated callouts, and generative AI driven summaries that surface key insights proactively.
- Implement data governance frameworks and quality control mechanisms, including automated validation, monitoring, and alerting to ensure data accuracy and reliability across all assets.
- Design and manage pipeline orchestration to coordinate data ingestion, transformation, and delivery across multiple systems and schedules.
- Partner with stakeholders across demand planning, forecasting, and inventory teams to translate business requirements into well scoped, long term, AI-driven data solutions.

About the team
We build the data infrastructure and analytics that powers decision making across demand planning, forecasting, sales, and inventory for Amazon Devices globally. Our core tables serve as the single source of truth for metrics used in leadership reviews, business planning cycles (OP1, OP2, QxG), and High Velocity Events like Prime Day. We are actively building AI enabled tools, including chat agents and automated reporting, and migrating our reporting to Quick. Our team values ownership, quality, and thinking big. We move fast, ship real products, and work closely with PL leaders, finance, science, and engineering teams to deliver insights that matter.

Basic Qualifications

- 10 years of professional or military experience
- 7 years of SQL, ETL or Oracle experience
- 7 years of processing large, multi-dimensional datasets from multiple sources experience
- 5 years of developing automated reporting experience
- Experience with AWS technologies
- Experience in scripting for automation (e.g. Python) and advanced SQL skills.
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Knowledge of data warehousing and data modeling
- Experience working directly with business stakeholders to translate between data and business needs

Preferred Qualifications

- Experience managing, analyzing and communicating results to senior leadership
- Experience programming to extract, transform and clean large (multi-TB) data sets
- Experience with theory and practice of information retrieval, data science, machine learning and data mining

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 for more information. If the country/region youre applying in isnt 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 />
USA, WA, Seattle - 130,400.00 - 176,300.00 USD annually

We're looking for a Senior Business Intelligence Engineer (BIE) to build AI-powered data products for Amazon Devices. You'll design and maintain MCP servers and semantic layers that make our core tables accessible to AI agents, automate daily business workflows (WBR narratives, flashes, executive summaries) using Gen. AI, and architect scalable data pipelines on AWS. This role sits at the intersection of analytics, data engineering, AI, and product development you'll define how machines understand our business data and scale that intelligence across multiple BI teams. Key job responsibilities- Design, build, and maintain scalable core data tables and pipelines that serve as the single source of truth for Devices sales, inventory, pricing and demand planning metrics.- Automate reporting workflows and data processes to reduce manual effort and improve speed, accuracy, and reliability of insights delivered to stakeholders.- Build and enhance Quick. Suite dashboards that provide self service analytics for product line leaders, finance, and supply chain teams.- Develop contextual data layers that connect disparate data sources into unified, business ready datasets, enabling deeper analysis and cross functional visibility.- Build and integrate AI powered features into BI solutions, including intelligent agents, automated callouts, and generative AI driven summaries that surface key insights proactively.- Implement data governance frameworks and quality control mechanisms, including automated validation, monitoring, and alerting to ensure data accuracy and reliability across all assets.- Design and manage pipeline orchestration to coordinate data ingestion, transformation, and delivery across multiple systems and schedules.- Partner with stakeholders across demand planning, forecasting, and inventory teams to translate business requirements into well scoped, long term, AI-driven data solutions. About the team. We build the data infrastructure and analytics that powers decision making across demand planning, forecasting, sales, and inventory for Amazon Devices globally. Our core tables serve as the single source of truth for metrics used in leadership reviews, business planning cycles (OP 1, OP 2, Qx. G), and High Velocity Events like Prime Day. We are actively building AI enabled tools, including chat agents and automated reporting, and migrating our reporting to Quick. Our team values ownership, quality, and thinking big. We move fast, ship real products, and work closely with PL leaders, finance, science, and engineering teams to deliver insights that matter. Basic Qualifications- 10 years of professional or military experience- 7 years of SQL, ETL or Oracle experience- 7 years of processing large, multi-dimensional datasets from multiple sources experience- 5 years of developing automated reporting experience- Experience with AWS technologies- Experience in scripting for automation (e.g. Python) and advanced SQL skills.- Experience with data visualization using Tableau, Quicksight, or similar tools- Knowledge of data warehousing and data modeling- Experience working directly with business stakeholders to translate between data and business needs. Preferred Qualifications- Experience managing, analyzing and communicating results to senior leadership- Experience programming to extract, transform and clean large (multi-TB) data sets- Experience with theory and practice of information retrieval, data science, machine learning and data mining.
search terms: Business+Science
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