Description

Job Description

Key job responsibilities
• Partner with Finance Operations leaders and process owners to frame business problems, define the right metrics, and deliver analytics that drive decisions.
• Own the insight layer end-to-end: write advanced SQL against curated Finance Operations data, build and maintain Amazon QuickSight dashboards.
• Design and ship AI-assisted analytics experiences, for example, natural-language Q&A over curated metrics, LLM-generated narratives for business reviews, anomaly summaries, and agentic workflows that automate repetitive analyst tasks.
• Build self-serve analytics products so that business teams can answer their own "what" and "why" questions without a ticket queue, using Amazon's internal GenAI tooling (Amazon Quick or Bedrock-backed assistants) layered on top of governed data.
• Define and enforce metric definitions as a custodian of the "single source of truth" in partnership with Data Engineering; provide technical input on upstream data models without owning the pipelines.
• Identify automation opportunities across reporting and analyst workflows; apply AI where it meaningfully reduces manual effort or improves quality, and measure the efficiency gains.
About the team
Global Accounts Receivable and Global Accounts Payable run all AR and AP processes across Amazon's businesses and geographies. Global Data Analytics (GDA) provides data, analytics, and insights to AR and AP. Our mission: "As trusted and business-focused analytics partners, we provide timely data, analytics, and insights across Service Centers and global functions. We are custodians of data and metric definitions. We apply science methods to large-scale transactional processes and use automation to improve efficiency." The GDA team partners with stakeholders across the globe and works alongside Data Engineering and Data Science peers. BIEs here focus on business analytics and AI-assisted insights.
Basic Qualifications
• 5+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
• 5+ years of Tableau Desktop, QuickSight or other relevant data visualization software experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience writing complex SQL queries
• Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
Preferred Qualifications
• Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
• Master's degree in BI, finance, engineering, statistics, computer science, mathematics or equivalent quantitative field

Key Skills

Education

Any Graduate