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
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-powe'red 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 (eg, 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 makingDesigning, 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 PL
- 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 Amazons benchmark organization.
- 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
- Bachelors degree in BI, fice, engineering, statistics, computer science, mathematics, fice or equivalent quantitative field
- Experience with Generative AI technologies, including prompt engineering, working with LLM APIs (eg, Amazon Bedrock, OpenAI, Anthropic), or building AI-powe'red analytics applications
- Familiarity with GenAI frameworks and tools such as LangChain, vector databases, or embedding models for semantic search and retrieval 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
- Masters degree in BI, fice, engineering, statistics, computer science, mathematics, fice or equivalent quantitative field
- Relentless curiosity and drive to explore emerging trends and technologies in the field
