Business Intelligence Engineer, WWPS Tech Team Ops

Amazon; Arlington (VA); On-site; USD 110,000 - 140,000; Full time

Job summary

Amazon Web Services (AWS) WWPS Reporting and Analytics team is seeking a Business Intelligence Engineer to analyze datasets and deliver actionable insights through dashboards and AI-powered narratives for the WWPS Tech Team. You will write and debug SQL queries to support decisions and collaborate with external reporting units on data standards and scalable solutions.

You will own data pipelines and production dashboards, and leverage AI-enabled tooling to accelerate workflows while documenting

Responsibilities

• Own the lifecycle of Quick assets (agents, apps, dashboards) and data pipelines from requirements to deployment
• Work with AI-powered tools and demonstrate how to integrate them into daily workflows
• Perform root-cause analyses and deep dives using SQL to answer business questions from sales leadership
• Serve as SME on reporting data models, metrics definitions, and KPIs
• Translate ambiguous requests into structured analytical approaches and scalable reporting
• Coordinate with external units to align data standards and delivery timelines
• Identify gaps in reporting coverage and propose solutions
• Develop and maintain technical documentation including data dictionaries, dashboards guides, and runbooks

Job description

Amazon Web Services (AWS) World-Wide Public Sector (WWPS) Reporting and Analytics team is seeking a Business Intelligence Engineer to support our Global Sales & Operations organizations. In this role, the ideal candidate will be responsible for analyzing datasets to identify actionable insights delivered through AI agents, chat bots, and narratives, while developing and maintaining production-level Quick dashboards and apps for the WWPS Tech Team organization. Additionally, this role will involve writing and debugging SQL queries to conduct deep-dive analyses in support of business decisions. This individual will collaborate with external reporting business units to support large-scale development efforts and work closely with project management teams to ensure proper guidance, use cases, and documentation are available to our Sales and Operations teams.

Key job responsibilities

Key responsibilities of the Business Intelligence Engineer role include:

• Owning the the lifecycle of Amazon Quick assets (i.e., agents, apps, dashboards) and data pipelines from requirements gathering through deployment and ongoing maintenance
• Experience working with AI-powered development tools (e.g., AI-assisted IDEs, code generation tools, or similar). Candidates should be comfortable leveraging AI tooling to accelerate their workflows and be able to speak to how they've integrated these technologies into their day-to-day work.
• Performing root-cause analyses and deep dives using SQL to answer complex business questions from sales leadership
• Serving as a subject matter expert on reporting data models, metrics definitions, and organizational KPIs
• Translating ambiguous business requests into structured analytical approaches and scalable reporting solutions
• Coordinating cross-functionally with external business units to align on shared data standards and delivery timelines for large initiatives
• Proactively identifying gaps in existing reporting coverage and proposing solutions to address emerging business needs
• Develop and maintain technical documentation including data dictionaries, dashboard user guides, and runbooks

A day in the life

The World-Wide Public Sector Reporting and Analytics Center of Excellence (RACE) builds the reporting infrastructure and analytical capabilities that empower our global Sales and Operations organizations to make data-driven decisions. We design scalable analytic solutions using AI, define organizational metrics, and deliver insights that drive business outcomes across public sector customers worldwide. Our team operates at the intersection of business intelligence, AI, data engineering, and stakeholder enablement — partnering closely with sales and tech leaders, operations teams, and cross-functional business units to ensure the right data reaches the right people at the right time.

About the team

About AWS

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