Amazon

Business Intelligence Engineer, RBS BE - BQA

Posted On

Jan. 13, 2026

Location

Chennai, Tamil Nadu

Experience Level

Freshers/Experienced

Job Type

Business Intelligence

Apply By

Feb. 24, 2026

Job 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 BQA

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 BQA transforms organizational capability through four pillars: Quality Assurance, People Excellence, Continuous Improvement, and Innovation. The team proactively solves internal challenges via systematic defect identification and data-driven frameworks. Through various programs, BQA positions RBS as Amazon's 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
- Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware

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