Description We are looking for a customer-obsessed Business Intel Engineer that thrives in a culture of data-driven decision making who will be responsible to help us hold a high bar for RBS ACES Key job responsibilities This individual will be responsible for driving/creating: - Leveraging Generative AI tools and Large Language Models (LLMs) to automate data analysis, generate insights, and create natural language summaries of complex datasets - Building and deploying GenAI-powered analytics solutions to enhance self-service capabilities and accelerate decision-making - Developing prompt engineering strategies and RAG (Retrieval-Augmented Generation) pipelines to integrate GenAI with existing data infrastructure - Experimenting with foundation models (e.g., Amazon Bedrock, SageMaker JumpStart) to solve business intelligence challenges - Experience working with large, multi-dimensional datasets from multiple sources - Make recommendations for new metrics, techniques, and strategies to improve the operational and quality metrics. - Proficient using at least one data visualization product (Tableau, Qlik, Amazon QuickSight, Power BI, etc.) - Experience in deployment of Machine Learning and Statistical models - Building new Python utilities and maintaining existing ones - Enabling more efficient adhoc queries & analysis - Working closely with research scientists, business analysts and product leads to scale data - Ensuring consistency between various platform, operational, and analytic data sources to enable faster and more efficient detection and resolution of issues - Exploring and learn the latest AWS technologies to provide new capabilities and increase efficiencies - Mentoring the team on analytics best practices A day in the life - Working closely with cross-functional teams including Product/Program Managers, Software Development Managers, Applied/Research/Data Scientists, and Software Developers - Building dashboards, performing root cause analysis, and sharing actionable insights with stakeholders to enable data-informed decision making - Leading reporting and analytics initiatives to drive data-informed decision making- Designing, developing, and maintaining ETL processes and data visualization dashboards using Amazon QuickSight - Transforming complex business requirements into actionable analytics solutions. About the team Retail Business Service accelerates WW Amazon Stores growth by improving customer and Selling Partner experiences while optimizing costs. Our three-fold charter: 1) Detect and fix customer shopping impediments, 2) Grow SP business profitably including scaled tier-2/3 management, 3) Reduce Cost-to-Serve across Stores P&L RBS ACES transforms organizational capability through four pillars: Org Excellence, People Excellence, Continuous Improvement, and Innovation. The team proactively solves internal challenges via systematic defect identification and data-driven frameworks. Through various programs, ACES positions RBS as Amazon's benchmark organization. Basic Qualifications - 5+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience - Experience with data visualization using Tableau, Quicksight, or similar tools - Experience with data modeling, warehousing and building ETL pipelines - Experience in Statistical Analysis packages such as R, SAS and Matlab - Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling - Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business - Experience writing complex SQL queries - Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field - Experience with Generative AI technologies, including prompt engineering, working with LLM APIs (e.g., Amazon Bedrock, OpenAI, Anthropic), or building AI-powered analytics applications - Familiarity with GenAI frameworks and tools such as LangChain, vector databases, or embedding models for semantic search and retrieval Preferred Qualifications - 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 - Master's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field - Relentless curiosity and drive to explore emerging trends and technologies in the field Our inclusive culture empowers Amazonians to deliver the best results for our customers. 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