Job Description
Join one of Amazons most impactful analytics organizations, empowering the worlds largest Accounts Receivable and Accounts Payable departments through advanced data capabilities and near real-time, actionable insights. Global Data Analytics (GDA) is the trusted analytics partner for Finance Operations, delivering data-driven solutions across global service centers and functions. We are looking for an exceptional Business Intelligence Engineer to own a high-visibility area within GDA. You will be a deeply analytical, business-obsessed BIE who translates ambiguous business problems into crisp analytical questions, answers them with data, and turns the answers into decisions. You will build dashboards, self-serve analytics, and AI-assisted insight products that are consumed by Finance Operations leaders across geographies. This is a role for someone who wants to sit close to the business, influence outcomes, and use AI as a force multiplier on traditional analytics.
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 QA 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 Amazons 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 Amazons 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.
- 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
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
- Masters degree in BI, finance, engineering, statistics, computer science, mathematics or equivalent quantitative field
Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Job Classification
Industry: Internet
Functional Area / Department: Data Science & Analytics
Role Category: Data Science & Analytics - Other
Role: Data Science & Analytics - Other
Employement Type: Full time
Contact Details:
Company: Amazon
Location(s): Hyderabad
Keyskills:
Computer science
Automation
Data modeling
Business analytics
Analytical
data visualization
Oracle
Data mining
Business intelligence
Python