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Business Intelligence Engineer, AWS DC Acqn&Construction

Amazon.com Inc
  • Seattle, WA
    2 days ago

    Job Description

    AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we're looking for talented people who want to help.

    You'll join a diverse team of technical program managers, design engineers, construction managers, network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

    Do you want to be an integral part of the world"s transition to the cloud? The ML Capacity Delivery Team (MLZ) is seeking a Business Intelligence Engineer II (BIE) with a combination of superior analytical abilities, business acumen, curiosity, technical skills, and strong written and verbal communication skills to join our team.

    The MLZ team is responsible for delivering ML and AI infrastructure capacity across AWS"s global data center footprint. As a BIE on this team, you will build the data foundations, reporting systems, and analytical capabilities that enable leadership to make critical decisions about how we plan, track, and deliver ML capacity at scale. You will work closely with technical program managers, systems engineers, operations teams, and planning organizations to transform complex operational data into actionable insights that drive delivery velocity and efficiency.

    Data-driven decision-making is at the core of Amazon"s culture, and people who are exceptionally talented at analyzing large sets of data to build insights are critical. Your work will directly impact the decisions and strategy of the ML Capacity Delivery organization and our customers. You will gather customer needs and insights, mine large and diverse data sets from across AWS Infrastructure, build visualizations and tools for our business partners, and generate insights to help senior leaders make critical business decisions. The successful BIE will not only possess the expertise and passion for analyzing data, designing metrics to measure the performance of the business, and building reporting capabilities and tools, but will also interact directly with business leaders and teams that rely on the metrics and analyses they produce.

    The ideal candidate must be a self-starter, comfortable with ambiguity, able to think big and be creative (while still paying careful attention to detail), and enjoy working in a fast-paced, dynamic environment. If you are excited about data, are results-oriented, and want to join a growing analytics team within Amazon - this role is for you!

    Key job responsibilities

    Design, develop, and maintain scaled, automated, user-friendly systems, reports, and dashboards that support ML capacity delivery tracking, planning, and operational decision-making.

    Build and optimize data pipelines for extraction, transformation, and loading (ETL) of data from diverse sources across AWS Infrastructure using SQL, Python, and AWS big data technologies.

    Apply deep analytic and business intelligence skills to extract meaningful insights from large and complex data sets related to capacity delivery timelines, supply chain logistics, and infrastructure deployment.

    Collaborate with program managers, systems engineers, and operations teams to understand business requirements and translate them into scalable data solutions and reporting capabilities.

    Build data visualizations that tell the story of ML capacity delivery performance - trends, patterns, bottlenecks, and outliers - through rich, intuitive dashboards for stakeholders at all levels.

    Design and track key performance metrics that measure the health and efficiency of ML capacity delivery operations, including delivery velocity, on-time performance, and pipeline throughput.

    Serve as a liaison between business and technical teams to achieve the goal of providing actionable insights into current business performance and ad hoc analyses to support future improvements or innovations.

    Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.

    Proactively identify opportunities to improve data quality, automate manual reporting processes, and enhance the analytical maturity of the team through predictive and prescriptive analytics.

    About the team

    • Why AWS*

    Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

    • Diverse Experiences*

    Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

    • Work/Life Balance*

    We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

    • Inclusive Team Culture*

    Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness.

    • Mentorship and Career Growth*

    We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

    Numbers & Facts

    LocationSeattle, 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

    • Amazon Web Services (AWS)unmatched
    • Analysis Skillsunmatched
    • Artificial Intelligence (AI)unmatched
    • Best Practicesunmatched
    • Big Dataunmatched
    • Business Intelligenceunmatched
    • Business Skillsunmatched
    • Cloud Computingunmatched
    • Communication Skillsunmatched
    • Constructionunmatched
    • Construction Engineeringunmatched
    • Customer/Client Researchunmatched
    • Data Analysisunmatched
    • Data Managementunmatched
    • Data Qualityunmatched
    • Data Setsunmatched
    • Data Visualizationunmatched
    • Database Extract Transform and Load (ETL)unmatched
    • Detail Orientedunmatched
    • Financial Analysisunmatched
    • Leadershipunmatched
    • Logisticsunmatched
    • Mentoringunmatched
    • Metricsunmatched
    • Network Architecture/Engineeringunmatched
    • Network Operations Centerunmatched
    • Operations Managementunmatched
    • Operations Planningunmatched
    • Performance Analysisunmatched
    • Performance Metricsunmatched
    • Predictive Modelingunmatched
    • Presentation/Verbal Skillsunmatched
    • Project/Program Managementunmatched
    • Python Programming/Scripting Languageunmatched
    • Quality Managementunmatched
    • Reporting Dashboardsunmatched
    • Reporting Skillsunmatched
    • SQL (Structured Query Language)unmatched
    • Safety Standardsunmatched
    • Startupunmatched
    • Supply Chainunmatched
    • System Operationsunmatched
    • Systems Analysisunmatched
    • Systems Engineeringunmatched
    • Technical Leadershipunmatched
    • Technical/Engineering Designunmatched
    • Test Designunmatched
    • Time Managementunmatched
    • Validation Documentationunmatched
    • Writing Skillsunmatched

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