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Business Intelligence Engineer, Supply Chain Innovation, Bulk Fulfillment

Job in Austin, Travis County, Texas, 78716, USA
Listing for: Amazon
Full Time position
Listed on 2026-02-08
Job specializations:
  • IT/Tech
    Data Analyst, Data Engineer, Data Warehousing, Business Systems/ Tech Analyst
Job Description & How to Apply Below

Overview

Job  |  Services LLC

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.

Responsibilities
  • Data Infrastructure & Analytics
    • Design and build scalable data pipelines synthesizing information from multiple sources:
      Asana, Slack, WBRs, MBRs, Quick Sight Topics, and operational systems (SCOT, AFT, MSP).
    • Create automated reporting mechanisms for Senior leadership providing weekly program health snapshots across all 12-13 work streams with clear status, risks, dependencies, and next steps.
    • Develop data quality frameworks ensuring accuracy and consistency across expanding network of 24 One DCs and 13 SDCs.
  • Business Intelligence & Decision Support
    • Create executive dashboards and one-pagers for Senior leadership with appropriate 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 to inform go/no-go decisions.
    • Build dependency mapping visualizations showing relationships between work streams, identifying critical paths and potential bottlenecks.
  • Predictive Modeling & Optimization
    • Build predictive models for capacity planning across distribution centers, forecasting volume, labor requirements, and equipment needs for site launch readiness assessments.
    • Develop selection optimization models identifying which bulk ASINs to onboard based on customer purchase patterns, inventory availability, SIOC eligibility, and profitability metrics.
    • Create demand forecasting models for bulk conversion rates leveraging internal signals and competitive intelligence.
  • Operational Metrics & Performance Analysis
    • Own end-to-end analytics for Quality (DEA - Delivery Estimate Accuracy), Speed (click-to-promise), and Cost (productivity rates: pick rate, pack rate, cartons per labor hour).
    • Conduct deep-dive root cause analysis when metrics degrade, synthesizing quantitative data with qualitative context.
    • Build comparative analytics showing bulk performance versus regular component ASIN fulfillment to quantify program impact.
  • Cross-Functional Collaboration
    • 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.
    • Work with finance teams on business case development, ROI modeling, and cost-benefit analysis for capital planning and site enablement investments.
    • 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, No

    SQL, 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, Dynamo

    DB, 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…

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