Business Intelligence Engineer, RBS ACES
Amazon•Published 7 days ago•First seen 6 days ago
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:
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.
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
- 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.
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