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Data Engineer II, OpsTech Team, OTS Anchor Team

Amazon.com Inc

  • Austin, TX
  • 6 days ago

    Highlights

    You will work at the intersection of large scale data processing and real world operational impact, creating intelligence that directly influences how Amazon fulfills millions of orders across fulfillment centers, Amazon Fresh, Prime Now, Lockers, Pantry, Amazon Campus, and other operational environments. You will design high performance data pipelines, create trusted data products, and work with Solution Architects, Data Engineers, Applied Scientists, and Business Intelligence Engineers to turn complex operational data into intelligence that can be used by both people and AI systems.

    Numbers & Facts

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

    Description

    Join OpsTech to build strategic data infrastructure powering Amazon's global operations technology ecosystem. OpsTech provides critical technology and data capabilities that support Amazon's customer commitment worldwide. You will work at the intersection of large scale data processing and real world operational impact, creating intelligence that directly influences how Amazon fulfills millions of orders across fulfillment centers, Amazon Fresh, Prime Now, Lockers, Pantry, Amazon Campus, and other operational environments.

    As a Data Engineer, you will build and evolve scalable data platforms that power analytics, machine learning, and AI driven experiences across Amazon's global fulfillment and maintenance networks. You will design high performance data pipelines, create trusted data products, and work with Solution Architects, Data Engineers, Applied Scientists, and Business Intelligence Engineers to turn complex operational data into intelligence that can be used by both people and AI systems.

    You will help shape modern data engineering practices across OpsTech, including automated data quality, observability, lineage, data contracts, orchestration, and intelligent pipeline operations. Your work will provide the trusted data foundation behind AI agents, machine learning systems, operational analytics, and automated decision making at global scale.

    This is a high impact individual contributor role with significant opportunity to expand your technical scope and influence how OpsTech builds the next generation of data and AI capabilities.

    Key job responsibilities

    • Build scalable data pipelines and platforms that transform complex operational data into trusted, AI ready data products.
    • Power AI agents, machine learning systems, and intelligent automation with reliable data, context, and semantic layers.
    • Develop batch and streaming architectures that deliver timely operational signals for analytics, detection, diagnosis, and decision making.
    • Create reusable datasets and data products that support analytics, experimentation, production models, and operational applications.
    • Build feature pipelines, training datasets, and production workflows that connect data engineering with machine learning and AI.
    • Improve platform reliability through automated data quality, observability, lineage, testing, and anomaly detection.
    • Design semantic models and metrics that give operators, leaders, analysts, and AI systems a consistent understanding of the business.
    • Partner with Data Scientists, ML Engineers, Business Intelligence Engineers, Solution Architects, Program Managers, and operations teams to deliver measurable business impact.
    • Raise the engineering bar by improving scalability, maintainability, governance, and development standards across OpsTech.
    • Explore emerging data and AI technologies and help shape the next generation of OpsTech data platforms.

    A day in the life

    You will work closely with Data Engineers, Data Scientists, ML Engineers, Business Intelligence Engineers, Solution Architects, Program Managers, and operations teams across OpsTech.

    Your day may include designing a new data pipeline, reviewing architecture for an AI powered application, improving the reliability of a critical dataset, or working with partners to understand an operational problem and turn it into a scalable data solution.

    You will spend time building and improving data products used by analysts, operators, leaders, machine learning systems, and AI agents. You may investigate data quality issues, optimize large scale processing workflows, improve observability, or develop new semantic models that make complex operational data easier to understand and use.

    You will also participate in design reviews, code reviews, technical discussions, and planning sessions while owning projects from initial problem definition through production launch.

    The problems are varied, technically challenging, and directly connected to how Amazon operates at global scale.

    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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