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Senior Data Engineer, WW Ops Finance - S&A

Amazon.com Inc
  • Irving, TX
    3 days ago

    Job Description

    Are you passionate about standardizing data platforms and automating data engineering to drive analytics and reporting? Do you excel in dynamic, fast-paced environments and find joy in converting data into actionable insights? Are you adept at implementing data governance practices and defining data access and quality standards? If you thrive in innovation and can deliver scalable Data Engineering Solutions, then the Worldwide Operations Finance Standardization & Automation (SnA) team has an exciting opportunity for you! We are seeking a customer-centric Senior Data Engineer to establish a reliable and accessible data platform, ensuring Operations Finance customers have complete trust in the data, technology, and tools to make data-driven business decisions.

    As a Senior Data Engineer in WW S&A, you will be working in one of the world"s largest and most complex data ecosystems. You will design, build, and own scalable data domains that serve as the foundational layer for the business. In this role, you will architect and implement robust, well-governed data domain models that integrate multi-heterogeneous data sources, enabling seamless consumption across a wide spectrum of use cases - including real-time and batch analytics, interactive dashboards and reporting, machine learning and predictive modeling, operational automation, API-driven data services, self-service exploration, and ad-hoc data requests. As a Sr. DE, you will define domain boundaries, establish data contracts, and curate high-quality, discoverable datasets that empower cross-functional teams to derive insights quickly and reliably, while ensuring data is aggregated, retrieved, and served in a fast, secure, and scalable manner across all consumption patterns. You should have excellent business and communication skills to be able to work with business owners, Product teams and Tech leaders to gather infrastructure requirements, design data infrastructure, build up data pipelines and data-sets to meet business needs. You will be responsible for designing, developing, and operating a data service platform using Python, Airflow, and SQL to build the various ETL, analytics, and data quality components. You'll automate deployments using AWS CodeDeploy, AWS CodePipeline, AWS Cloud Development Kit (CDK), and AWS Cloud Formation. You will work with AWS services like Redshift, Glue, S3, IAM, CloudWatch, and more.

    Key job responsibilities

    Key job responsibilities

    • Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using Python, SQL and AWS big data technologies.
    • Explore and learn the latest AWS technologies to provide new capabilities and increase efficiencies of the team.

    Designing and implementing complex pipelines and other Data Engineering solutions.

    • Work closely with business owners, developers, Business Intelligence Engineer to explore new data sources and deliver the data.
    • Create extensible designs and easy to maintain solutions with the long term vision in mind
    • Improve tools, processes, scale existing solutions, create new solutions as required based on team and stakeholder needs
    • Familiar with AI Delivery Life Cycle (DLC), contributing to the end-to-end process of delivering AI-powered solutions - from ideation and data preparation through model development, deployment, monitoring, and iteration.

    Numbers & Facts

    LocationIrving, TX
    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

    • Amazon Simple Storage Service (S3)unmatched
    • Amazon Web Services (AWS)unmatched
    • Application Programming Interface (API)unmatched
    • Artificial Intelligence (AI)unmatched
    • Automationunmatched
    • Big Dataunmatched
    • Business Intelligenceunmatched
    • Cloud Computingunmatched
    • Communication Skillsunmatched
    • Cross-Functionalunmatched
    • Data Collectionunmatched
    • Data Managementunmatched
    • Data Modelingunmatched
    • Data Qualityunmatched
    • Data Setsunmatched
    • Database Extract Transform and Load (ETL)unmatched
    • Ecosystemsunmatched
    • Emerging Technologyunmatched
    • Financeunmatched
    • International Operationsunmatched
    • Machine Learningunmatched
    • Predictive Modelingunmatched
    • Process Improvementunmatched
    • Python Programming/Scripting Languageunmatched
    • Quality Metricsunmatched
    • Reporting Dashboardsunmatched
    • Requirements Managementunmatched
    • SQL (Structured Query Language)unmatched
    • Scalable System Developmentunmatched
    • Use Casesunmatched
    • Web Analyticsunmatched

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