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Software Development Engineer II , Amazon Fulfillment Technologies - Inbound

Amazon.com Inc
  • Bellevue, WA
    8 days ago

    Job Description

    Amazon Fulfillment Technologies (AFT) Inbound builds the systems that move inventory into Amazon"s fulfillment network at massive scale. We"re looking for a Software Development Engineer II with deep data engineering expertise to independently own the large-scale data infrastructure that powers intelligent decision-making across the inbound supply chain. You"ll design and build the batch and streaming pipelines, data models, and processing systems that turn petabytes of raw supply-chain data into reliable, well-governed datasets. You"ll partner closely with Applied and Research Scientists to feed and productionize Machine Learning (ML) systems, and you"ll raise the engineering bar for how the team builds and operates data at scale.

    Key job responsibilities

    • Independently design, build, and operate scalable, reliable data pipelines (batch and streaming) that ingest, transform, and serve large volumes of supply-chain data.
    • Own data modeling, data warehousing, and the design of curated datasets that serve analytics, reporting, and Machine Learning (ML) use cases.
    • Build and maintain feature engineering pipelines and feature stores that supply ML models with high-quality, low-latency data.
    • Lead design reviews and make sound technical trade-offs across performance, cost, scalability, and operational complexity for your area of ownership.
    • Own data quality, lineage, and observability across the datasets, pipelines, and services you build, and drive systemic improvements to reliability.
    • Partner with Applied and Research Scientists to operationalize ML workflows, including feature delivery, training data preparation, and model-scoring pipelines.
    • Deliver robust, well-tested, production-quality software and drive engineering best practices (code reviews, Continuous Integration/Continuous Deployment (CI/CD), monitoring, operational excellence).
    • Diagnose and resolve complex production and data issues; participate in on-call and reduce operational load through automation.
    • Mentor SDE I and early-career engineers and influence the technical roadmap for the team"s data platform.

    About the team

    Amazon Fulfillment Technologies (AFT) Inbound builds the software and science that move inventory into Amazon"s fulfillment network - from the moment a supplier ships product to the point it"s received, stowed, and ready to fulfill customer orders. Operating at the scale of billions of units across a global network of fulfillment centers, our team owns the data infrastructure and intelligent systems that make inbound flow faster, more accurate, and more cost-efficient. We work at the intersection of large-scale data engineering and applied Machine Learning (ML), partnering closely with Applied and Research Scientists to turn petabytes of supply-chain data into decisions that ship every day. If you"re excited by hard distributed-systems problems, real-world scale, and building the data foundations that power automation and optimization across Amazon"s supply chain, you"ll find a high-ownership, high-impact home here.

    Numbers & Facts

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

    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

    Skills

    • Automationunmatched
    • Best Practicesunmatched
    • Code Reviewsunmatched
    • Continuous Deployment/Deliveryunmatched
    • Continuous Integrationunmatched
    • Data Managementunmatched
    • Data Modelingunmatched
    • Data Qualityunmatched
    • Data Setsunmatched
    • Data Warehousingunmatched
    • Distributed Computingunmatched
    • Identify Issuesunmatched
    • Machine Learningunmatched
    • Mentoringunmatched
    • On Callunmatched
    • Order/Customer Fulfillmentunmatched
    • Process Improvementunmatched
    • Product Shipmentsunmatched
    • Production Machiningunmatched
    • Reliability Engineeringunmatched
    • Scalable System Developmentunmatched
    • Scientific Researchunmatched
    • Software Developmentunmatched
    • Software Engineeringunmatched
    • Supply Chainunmatched
    • Training Data Setsunmatched
    • Use Casesunmatched
    • Workload Automationunmatched

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