The posting
Come be a part of a rapidly expanding $50 billion-dollar global business on its trajectory to $100B. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech, retail, and generative AI in the B2B space — developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination, and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential.
The Amazon Business Flywheel Inputs (ABFI) Analytics team is looking for a Business Intelligence Engineer to build the measurement, reporting, and analytics foundations that power data-driven decisions and emerging generative AI experiences. Amazon Business (AB) represents an incredible opportunity to address a vast new market segment and customer base for Amazon. We are focused on building solutions that enable B2B customers to find and buy products and services across multiple devices and marketplaces. Our team owns the measurement and analytics strategy for key AB problems including price optimization, selection expansion, operational excellence, and AI-powered customer experiences. Amazon Business is one of Amazon's fastest-growing business sectors. We need builders who can think big, dive deep, and translate complex data into actionable business insights. Come work with us if you are customer-obsessed, analytical, and excited about making history.
As a Business Intelligence Engineer, you will partner closely with Product Managers, Software Developers, Applied Scientists, and business leaders to define success metrics, build scalable reporting solutions, and drive strategic decision making. You will develop robust data models and visualization products that enable stakeholders to monitor business performance, identify opportunities, and understand the impact of product and operational investments. The ideal candidate possesses strong business judgment, advanced SQL and analytical skills, expertise in data visualization and storytelling, experience conducting deep-dive investigations, and a passion for transforming complex datasets into clear and actionable insights. Experience leveraging generative AI tools to accelerate analysis, insight generation, and stakeholder self-service is highly valued.
In this role, you will establish measurement frameworks and KPI definitions that guide product and business decisions. You will partner with engineering and product teams to ensure high-quality telemetry is captured for existing and future product launches, enabling robust performance measurement and experimentation. You will design scalable reporting architectures, executive-facing dashboards, and self-service analytics solutions that integrate across Amazon Business Pricing, Selection, Managed Spend, and AI initiatives. You will drive root-cause analyses on ambiguous business problems, uncover strategic opportunities through deep analytical investigations, and influence the organization's approach to measurement, attribution, and data-driven decision making. You will also help shape the analytics foundations that power both traditional business intelligence and next-generation AI agent experiences.
Key job responsibilities * Designing, implementing, and maintaining scalable reporting solutions, dashboards, and analytics frameworks that provide visibility into key business and product performance metrics.
* Partnering with Scientists, Product Managers, Software Engineers, and business stakeholders to define KPIs, establish measurement methodologies, and develop trusted source-of-truth datasets for decision-making.
* Building and maintaining robust reporting pipelines, automated data validation processes, and monitoring mechanisms to ensure accuracy, consistency, and timeliness of business insights.
* Developing scalable data models, semantic layers, and self-service analytics solutions that enable stakeholders to explore data independently and integrate insights across multiple business domains — including datasets that support AI-powered analytics and agent experiences.
* Driving deep-dive analyses, root-cause investigations, and opportunity sizing exercises to uncover actionable insights and influence strategic business decisions.
* Designing executive-facing visualizations, business reviews, and performance reporting mechanisms that communicate complex findings through clear data storytelling.
* Establishing best practices for metric governance, experimentation measurement, attribution, and analytics engineering to improve trust and consistency across reporting ecosystems.
About the team Today, AB serves millions of business customers worldwide — from Fortune 500 enterprises and hospital systems to local governments and small businesses — and is on a trajectory to become a $100B business.
The Amazon Business Flywheel Inputs (ABFI) Data & Analytics team is the engine behind the data-driven decisions that power AB's growth flywheel. We own the metrics, insights, and data platforms that drive three of AB's most critical levers: Pricing Competitiveness, Selection Expansion, and Availability Optimization — across multiple marketplaces worldwide.
- Bachelor's degree or above in BI, finance, engineering, statistics, computer science, mathematics or equivalent quantitative field - 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience - 3+ years of using SQL, ETL (Extract, Transform, Load), or Oracle experience - 2+ years of Tableau Desktop, Quicksight or other relevant data visualization software experience - Experience with data modeling, warehousing and building ETL pipelines - Knowledge of Microsoft Excel at an advanced level, including: pivot tables, macros, index/match, vlookup, VBA, data links, etc.
- Master's degree or above in BI, finance, engineering, statistics, computer science, mathematics or equivalent quantitative field - Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets - Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift - Experience with statistical analytics and programming languages such as R, Python, Ruby, etc.
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