Business Intelligence Engineer, Supply Chain Innovation, Bulk Fulfillment

Amazon; Bellevue (WA); On-site; USD 99,500 - 160,000; Full time

Job summary

Amazon in Bellevue, WA is seeking a Business Intelligence Engineer to drive data-informed decisions for bulk fulfillment expansion. You will translate complex data into actionable insights shaping retail strategy and site launches.

You will own end-to-end analytics across multiple workstreams, build predictive models for capacity planning, and deliver executive dashboards to Senior leadership. This role offers end-to-end exposure across supply chain and global collaboration.

Qualifications

• 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience.
• 1+ years of SQL, ETL or Oracle experience.
• 1+ years of processing large, multi-dimensional datasets from multiple sources experience.
• 1+ years of performing statistical analysis experience.
• 1+ years of developing automated reporting 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

Responsibilities

• Design and build scalable data pipelines synthesizing information from multiple sources (Asana, Slack, WBRs, MBRs, QuickSight Topics, SCOT, AFT, MSP).
• Create automated reporting mechanisms for Senior leadership providing weekly program health snapshots across all workstreams with status, risks, dependencies, and next steps.
• Develop data quality frameworks ensuring accuracy and consistency across 24 One DCs and 13 SDCs.
• Create executive dashboards and one-pagers for Senior leadership with context for first-time readers, including trade-offs, risks, and stakeholder implications.
• Develop site launch readiness scorecards combining operational metrics, technical readiness, capacity data, and risk assessments for go/no-go decisions.
• Build dependency mapping visualizations showing relationships between workstreams and bottlenecks.
• Build predictive models for capacity planning across distribution centers, forecasting volume, labor requirements, and equipment needs.
• Develop selection optimization models identifying which bulk ASINs to onboard based on purchase patterns, inventory, SIOC eligibility, profitability.
• Create demand forecasting models for bulk conversion rates leveraging internal signals and competitive intelligence.
• Own end-to-end analytics for Quality, Speed, and Cost pillars; conduct root cause analysis; build comparative analytics.

Skills

Redshift

Oracle

NoSQL

SQL

ETL

Statistical analysis

Automated reporting

Tableau

Quicksight

Python

R

SAS

Matlab

Tools

Tableau

Quicksight

Python

R

SAS

Matlab

Job description

Description

Imagine revolutionizing how millions of customers shop for bulk products by creating effective data solutions that drive strategic decisions. As a Business Intelligence Engineer, you'll be the critical analytical force behind Amazon's ambitious expansion into bulk fulfillment, translating complex data into actionable insights that shape the future of retail.

This role offers comprehensive end-to-end exposure across Amazon's supply chain, from vendor inbound through customer delivery, with direct impact on a strategic initiative that will reshape customer perception of Amazon as a destination for bulk purchases.

Key job responsibilities

Data Infrastructure & Analytics

1. Design and build scalable data pipelines synthesizing information from multiple sources: Asana (task management), Slack (real-time updates), WBRs (weekly operations), MBRs (monthly business reviews), QuickSight Topics (live metrics), and operational systems (SCOT, AFT, MSP)

2. Create automated reporting mechanisms for Senior leadership providing weekly program health snapshots across all 12-13 workstreams with clear status, risks, dependencies, and next steps

3. Develop data quality frameworks ensuring accuracy and consistency across expanding network of 24 One DCs and 13 SDCs

Business Intelligence & Decision Support

1. Create executive dashboards and one-pagers for Senior leadership with appropriate context for first-time readers, including trade-offs, risks, and stakeholder implications

2. Develop site launch readiness scorecards combining operational metrics, technical readiness, capacity data, and risk assessments to inform go/no-go decisions

3. Build dependency mapping visualizations showing relationships between workstreams, identifying critical paths and potential bottlenecks

Predictive Modeling & Optimization

1. Build predictive models for capacity planning across distribution centers, forecasting volume, labor requirements, and equipment needs for site launch readiness assessments

2. Develop selection optimization models identifying which bulk ASINs to onboard based on customer purchase patterns, inventory availability, SIOC eligibility, and profitability metrics

3. Create demand forecasting models for bulk conversion rates (single-unit to bulk purchases) leveraging internal signals and competitive intelligence

Operational Metrics & Performance Analysis

1. Own end-to-end analytics for three critical pillars: Quality (DEA - Delivery Estimate Accuracy), Speed (click-to-promise), and Cost (productivity rates: pick rate, pack rate, cartons per labor hour)

2. Conduct deep-dive root cause analysis when metrics degrade, synthesizing quantitative data (miss units by site/day/attribution) with qualitative context (WBR narratives, Slack discussions, operational feedback)

3. Build comparative analytics showing bulk performance versus regular component ASIN fulfillment to quantify program impact

Cross-Functional Collaboration

1. Partner with Product Management, Supply Chain, Operations, and Technology teams across 10+ VP organizations to define metrics, validate data accuracy, and translate business questions into analytical frameworks

2. Work with finance teams on business case development, ROI modeling, and cost-benefit analysis for capital planning and site enablement investments

3. Collaborate with international teams (Canada, EU) to establish consistent metrics definitions and reporting standards for geographic expansion

Basic Qualifications

• 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience

• 1+ years of SQL, ETL or Oracle experience

• 1+ years of processing large, multi-dimensional datasets from multiple sources experience

• 1+ years of performing statistical analysis experience

• 1+ years of developing automated reporting 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

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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits .

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