Business Intelligence Engineer, WWPS Tech Team Ops

About the role

The World-Wide Public Sector Reporting and Analytics team is seeking a Business Intelligence Engineer to support Global Sales & Operations organizations. The ideal candidate will analyze datasets, develop and maintain production-level Quick dashboards and apps, and write SQL queries for deep-dive analyses.

Responsibilities

• Owning the lifecycle of Amazon Quick assets (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)
• 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
• Collaborating 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
• Developing and maintaining technical documentation including data dictionaries, dashboard user guides, and runbooks

Requirements

• 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc.
• 3+ years of SQL, ETL or Oracle experience
• 3+ years of processing large, multi-dimensional datasets from multiple sources
• 3+ years of developing automated reporting experience

Qualifications

• 3+ years of in the job offered or a related occupation experience
• Experience using Python scripting to process data for modeling
• 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
• Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage