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Business Intelligence Engineer, Amazon Intermodal

Amazon.com Inc

  • Atlanta, GA
  • 9 days ago

    Highlights

    The ideal candidate combines strong technical skills in SQL, data engineering, and statistical analysis with genuine curiosity about the business, and thrives in a fast-paced environment where the quality and speed of your analytics directly shape where the network invests to reduce cost and improve efficiency. This is a hands-on role responsible for transforming complex, high-volume supply chain data into automated pipelines, self-service dashboards, and deep-dive analyses that surface cost reduction opportunities and drive operational decisions.

    Numbers & Facts

    LocationAtlanta, GA
    IndustryRetail
    Company Size10,000 employees or more
    Year Founded1994
    Websitehttp://Amazon.com/militaryroles

    Description

    Amazon"s Intermodal (AZIM) Network Optimization team is looking for a Business Intelligence Engineer to build the data foundation and analytical tooling that powers cost optimization across the intermodal network. This is a hands-on role responsible for transforming complex, high-volume supply chain data into automated pipelines, self-service dashboards, and deep-dive analyses that surface cost reduction opportunities and drive operational decisions.

    Working closely with product managers, supply chain managers, and business stakeholders, you"ll own the end-to-end analytics lifecycle - from data modeling and ETL development to visualization and insight generation. The ideal candidate combines strong technical skills in SQL, data engineering, and statistical analysis with genuine curiosity about the business, and thrives in a fast-paced environment where the quality and speed of your analytics directly shape where the network invests to reduce cost and improve efficiency.

    Key job responsibilities

    Data Pipeline & Infrastructure Design, build, and maintain scalable ETL pipelines and data models that consolidate intermodal cost, volume, and operational data into reliable, query-ready datasets.

    Dashboards & Self-Service Analytics Develop and maintain automated dashboards and reporting mechanisms that give stakeholders real-time visibility into cost drivers, network performance, and optimization opportunities - reducing manual reporting effort.

    Deep-Dive Analysis Conduct rigorous analyses on cost trends, operational inefficiencies, and network anomalies to identify root causes and quantify savings opportunities. Translate raw data into clear, actionable recommendations.

    Metrics & Data Quality Define, instrument, and monitor key business metrics. Establish data quality checks and validation frameworks to ensure analytics are accurate and trusted across the org.

    Automation & Tooling Identify manual, repetitive analytical workflows and automate them - building reusable tools and queries that scale the team"s analytical capacity.

    Cross-Functional Partnership Partner with Product, Supply Chain Managers, Finance, and Operations to understand analytical needs, prioritize requests, and deliver data solutions that inform cost optimization decisions.

    A day in the life

    You"ll start each morning validating overnight data pipeline runs and checking dashboards for anomalies or data quality issues. From there, you"ll dig into an analytical deep dive - querying large datasets to size a cost savings opportunity, investigating a network anomaly, or building a new metric requested by the team. You"ll partner with Product Managers and Supply Chain Managers to translate business questions into data solutions, and collaborate with Finance to align on cost baselines and definitions. You"ll spend time building - writing ETL code, refining data models, or automating a manual report. When you uncover an insight, you"ll package it into a clear visualization or write-up for stakeholders and leadership.

    About Company

    At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

    Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

    It’s Always Day 1
    At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

    Our Leadership Principles
    Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

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