Business Intelligence Engineer

DESCRIPTION

We are seeking a customer-obsessed Business Intelligence Engineer who thrives in a data-driven decision-making culture to maintain a high standard for RBS BQA (Retail Business Service Business Quality Assurance).

Key Job Responsibilities:

• Leverage Generative AI tools and Large Language Models (LLMs) to automate data analysis, generate insights, and create natural language summaries of complex datasets.
• Build and deploy GenAI-powered analytics solutions to enhance self-service capabilities and accelerate decision-making.
• Develop prompt engineering strategies and RAG (Retrieval-Augmented Generation) pipelines to integrate GenAI with existing data infrastructure.
• Experiment with foundation models such as Amazon Bedrock and SageMaker JumpStart to address business intelligence challenges.
• Work with large, multi-dimensional datasets from multiple sources.
• Make recommendations for new metrics, techniques, and strategies to improve operational and quality metrics.
• Utilize at least one data visualization product, such as Tableau, Qlik, Amazon QuickSight, or Power BI.
• Deploy Machine Learning and Statistical models.
• Build new Python utilities and maintain existing ones.
• Enable more efficient ad-hoc queries and analysis.
• Collaborate closely with research scientists, business analysts, and product leads to scale data.
• Ensure consistency across various platform, operational, and analytical data sources to enable faster and more efficient detection and resolution of issues.
• Explore and learn the latest AWS technologies to introduce new capabilities and increase efficiencies.
• Mentor the team on analytics best practices.

A Day in the Life:

• Work closely with cross-functional teams including Product/Program Managers, Software Development Managers, Applied/Research/Data Scientists, and Software Developers.
• Build dashboards, perform root cause analysis, and share actionable insights with stakeholders to facilitate data-informed decision-making.
• Lead reporting and analytics initiatives to drive data-informed decision-making.
• Design, develop, and maintain ETL processes and data visualization dashboards using Amazon QuickSight.
• Transform complex business requirements into actionable analytics solutions.

About the Team:

Retail Business Service (RBS) drives worldwide Amazon Stores growth by enhancing customer and Selling Partner experiences while optimizing costs. Our charter includes: 1) Detecting and fixing customer shopping impediments, 2) Growing Selling Partner business profitably, and 3) Reducing Cost-to-Serve across the Stores P&L. RBS BQA enhances organizational capability through four pillars: Quality Assurance, People Excellence, Continuous Improvement, and Innovation. The team proactively solves internal challenges using systematic defect identification and data-driven frameworks, positioning RBS as a benchmark organization within Amazon.

BASIC QUALIFICATIONS:

• 5+ years of experience analyzing and interpreting data with Redshift, Oracle, NoSQL, etc.
• Experience with data visualization using Tableau, Quicksight, or similar tools.
• Experience with data modeling, warehousing, and building ETL pipelines.
• Experience with Statistical Analysis packages such as R, SAS, and Matlab.
• Experience using SQL to extract data from databases or data warehouses and scripting experience (Python) for data processing in modeling.
• Experience developing and presenting recommendations for new metrics to better understand business performance.
• Experience writing complex SQL queries.
• Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance, or an equivalent quantitative field.
• Experience in machine learning, data mining, information retrieval, statistics, or natural language processing, OR experience developing and deploying LLMs in production on GPUs, Neuron, TPU, or other AI acceleration hardware.

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 an equivalent quantitative field.
• Experience with design & innovation and research & development.

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