Business Intelligence Engineer, Amazon Wholesale
Amazon•Published 18 hours ago•First seen 1 hours ago
Amazon Wholesale India Private Limited (AWIPL) is looking for a Business Intelligence Engineer I to build the data foundation that supports our product, business, and operational decisions.
AWIPL works across wholesale and business-to-business commerce, including pricing and promotions, demand planning, buying, inventory management, fulfillment, returns, liquidation, vendor experience, and distribution. These programs generate data across multiple systems and business processes. The Business Intelligence Engineer will convert this data into reliable metrics, automated reports, dashboards, and actionable insights.
In this role, you will work with Product, Business, Finance, Operations, and Technology teams to understand business questions and translate them into scalable business intelligence solutions. You will use SQL, data visualization tools, and scripting languages to build datasets, automate recurring reports, investigate performance gaps, and measure the results of product launches and operational changes.
The successful candidate will have strong analytical judgment, attention to detail, and the ability to explain data clearly. You will be comfortable working with large datasets, identifying data-quality issues, and reconciling differences between business and technical definitions. You will learn AWIPL’s end-to-end business processes and help teams use consistent, trusted information to make decisions.
Key job responsibilities
Build and maintain SQL datasets, reports, dashboards, and recurring business-review mechanisms for AWIPL programs.
Develop metrics across selection, pricing, promotions, forecasting, buying, inventory, fulfillment, returns, liquidation, vendor experience, and distribution.
Work with stakeholders to document metric definitions, business rules, data sources, ownership, and refresh schedules.
Automate manual data extraction, reconciliation, and reporting processes.
Analyze business and operational performance, identify trends and anomalies, and conduct root-cause analysis.
Establish data-quality checks and investigate discrepancies across source systems, dashboards, and financial or operational reports.
Support product launches by defining success metrics, establishing baselines, validating instrumentation, and measuring post-launch results.
Support user acceptance testing by validating data flows, business rules, and expected outputs.
Develop self-service dashboards that allow stakeholders to monitor performance by product, vendor, category, location, program, and other relevant dimensions.
Partner with Product Managers, Business Analysts, Software Development Engineers, Data Engineers, Finance, and Operations teams to translate requirements into BI deliverables.
Prepare clear written summaries and visualizations that explain findings, limitations, and recommended actions.
Maintain documentation for datasets, queries, dashboards, and recurring reporting processes.
Protect confidential business information and apply appropriate access controls when working with sensitive datasets.
A day in the life
You may start the day by reviewing a dashboard and investigating an unexpected change in inventory availability or forecast accuracy. You could work with a Product Manager to define the measurement plan for a pricing or supply-chain launch, write SQL to reconcile data across source systems, and add automated validation checks to a recurring report.
Later, you may review metric definitions with Finance and Operations partners, publish a QuickSight dashboard for a business review, or summarize the drivers behind a performance gap. You will balance recurring reporting needs with scoped analytical projects and automation opportunities. Senior Business Intelligence Engineers, Data Engineers, and business partners will provide guidance on larger or less-defined problems.
About the team
The AWIPL Product team builds capabilities that support wholesale and B2B commerce in India. Our work spans customer-facing pricing and promotions, supply-chain planning, buying, inventory health, fulfillment, returns, liquidation, vendor tools, distribution, and the adoption of relevant worldwide Amazon capabilities.
We work across business and technical boundaries. Our decisions require a shared understanding of customer outcomes, operational performance, financial impact, and system behavior. The Business Intelligence Engineer will help establish this shared understanding through trusted data, consistent metrics, and repeatable analytical mechanisms.
AWIPL works across wholesale and business-to-business commerce, including pricing and promotions, demand planning, buying, inventory management, fulfillment, returns, liquidation, vendor experience, and distribution. These programs generate data across multiple systems and business processes. The Business Intelligence Engineer will convert this data into reliable metrics, automated reports, dashboards, and actionable insights.
In this role, you will work with Product, Business, Finance, Operations, and Technology teams to understand business questions and translate them into scalable business intelligence solutions. You will use SQL, data visualization tools, and scripting languages to build datasets, automate recurring reports, investigate performance gaps, and measure the results of product launches and operational changes.
The successful candidate will have strong analytical judgment, attention to detail, and the ability to explain data clearly. You will be comfortable working with large datasets, identifying data-quality issues, and reconciling differences between business and technical definitions. You will learn AWIPL’s end-to-end business processes and help teams use consistent, trusted information to make decisions.
Key job responsibilities
Build and maintain SQL datasets, reports, dashboards, and recurring business-review mechanisms for AWIPL programs.
Develop metrics across selection, pricing, promotions, forecasting, buying, inventory, fulfillment, returns, liquidation, vendor experience, and distribution.
Work with stakeholders to document metric definitions, business rules, data sources, ownership, and refresh schedules.
Automate manual data extraction, reconciliation, and reporting processes.
Analyze business and operational performance, identify trends and anomalies, and conduct root-cause analysis.
Establish data-quality checks and investigate discrepancies across source systems, dashboards, and financial or operational reports.
Support product launches by defining success metrics, establishing baselines, validating instrumentation, and measuring post-launch results.
Support user acceptance testing by validating data flows, business rules, and expected outputs.
Develop self-service dashboards that allow stakeholders to monitor performance by product, vendor, category, location, program, and other relevant dimensions.
Partner with Product Managers, Business Analysts, Software Development Engineers, Data Engineers, Finance, and Operations teams to translate requirements into BI deliverables.
Prepare clear written summaries and visualizations that explain findings, limitations, and recommended actions.
Maintain documentation for datasets, queries, dashboards, and recurring reporting processes.
Protect confidential business information and apply appropriate access controls when working with sensitive datasets.
A day in the life
You may start the day by reviewing a dashboard and investigating an unexpected change in inventory availability or forecast accuracy. You could work with a Product Manager to define the measurement plan for a pricing or supply-chain launch, write SQL to reconcile data across source systems, and add automated validation checks to a recurring report.
Later, you may review metric definitions with Finance and Operations partners, publish a QuickSight dashboard for a business review, or summarize the drivers behind a performance gap. You will balance recurring reporting needs with scoped analytical projects and automation opportunities. Senior Business Intelligence Engineers, Data Engineers, and business partners will provide guidance on larger or less-defined problems.
About the team
The AWIPL Product team builds capabilities that support wholesale and B2B commerce in India. Our work spans customer-facing pricing and promotions, supply-chain planning, buying, inventory health, fulfillment, returns, liquidation, vendor tools, distribution, and the adoption of relevant worldwide Amazon capabilities.
We work across business and technical boundaries. Our decisions require a shared understanding of customer outcomes, operational performance, financial impact, and system behavior. The Business Intelligence Engineer will help establish this shared understanding through trusted data, consistent metrics, and repeatable analytical mechanisms.
Basic Qualifications
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- Experience with scripting language (e.g., Python, Java, or R)
Preferred Qualifications
- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis