BIE II, Tax

About the Role

The Business Intelligence Engineer (BIE) II in Global Tax Data (GTD) will build analytics datasets and data mart/warehouses, driving data analysis, reconciliation operations, root-cause investigations, and process improvements to support Amazon's monthly tax compliance cycles. This role involves partnering with customers in tax compliance and accounting, as well as stakeholders across finance technology, Data Engineering, Software Engineering, and Solutions Architects to ensure data completeness, accuracy, and timeliness for every filing.

Key Responsibilities

• Build and own the gold-standard data mart/warehouse for business reporting and analysis.
• Perform hands-on reconciliation and detailed analysis of large financial datasets, investigating and resolving discrepancies.
• Troubleshoot data quality issues, identify root causes, and drive corrective actions.
• Partner with compliance and customer teams to understand reporting requirements and translate business objectives into data specifications.
• Develop and maintain operational reports, dashboards, and metrics for reconciliation health and data readiness.
• Identify and implement improvements for efficiency, controllership, and data quality, including automating manual processes and coaching customer teams.
• Own and manage SIM tickets and intake workflows.
• Support audit data requests by extracting, validating, and delivering data packages.
• Document standard operating procedures, runbooks, and process flows.
• Build relationships with technology providers and technical teams, explaining financial and technical concepts to various audiences.
• Contribute to Monthly and Quarterly Business Reviews (MBRs/QBRs) and operational readiness activities.

Requirements & Tech Stack

• Redshift, Oracle, NoSQL
• Tableau, Quicksight, or similar data visualization tools
• Data modeling, warehousing, and ETL pipeline development
• SQL for data extraction
• Python scripting for data processing
• Excel (including VBA, pivot tables, array functions, power pivots)

Qualifications

• Experience in analyzing and interpreting data.
• Experience with data visualization.
• Experience with data modeling, warehousing, and building ETL pipelines.
• Experience using SQL to pull data from a database or data warehouse.
• Scripting experience (e.g., Python) to process data for modeling.
• Experience in the data/BI space.
• Experience in tax, finance, or a related analytical field.
• Experience defining requirements and using data and metrics to draw business insights.
• Experience making business recommendations and influencing stakeholders.
• Bachelor's degree in finance, accounting, business, economics, engineering, analytics, mathematics, statistics, or a related technical or quantitative field.
• Eagerness to learn new content quickly and venture into unfamiliar territory.
• Strong judgment and integrity when handling confidential information.

Preferred Qualifications

• Experience in data mining, ETL, and using databases in a business environment with large-scale, complex datasets.