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Job Opening: Data Engineer I – Business Intelligence


Position: Data Engineer I – Business Intelligence
Company: Amazon Corporate LLC
Location: Austin TX US

Be a part of what sets Amazon apart from everyone else! Join the power behind Prime.
Supply Chain Optimization Technologies (SCOT) creates the science and technology to drive Amazon’s supply chain. SCOT builds software systems to make the most products available to the most people for delivery as quickly as possible. The SCOT Austin teams focus on improving the promises we make to Amazon customers, defining what is available with 2-day Prime shipping, optimizing fulfillment costs, consolidating multiple orders into a single shipment, predicting future supply and demand, and creating the execution plan for our global fulfillment network. To accomplish these goals we build simulation and experimentation systems at scale and leverage cutting-edge technologies across Operations Research, Software Engineering, Machine Learning, Forecasting, and Linear Programming.
Watch this short video for more on SCOT: bit.ly/amazon-scot

    • Amazon is seeking an outstanding Data Engineer to join the Supply Chain Optimization Technologies (SCOT) Business Intelligence Team. Amazon.com has culture of data-driven decision-making, and demands business intelligence that is timely, accurate, and actionable. If you join the Amazon.com’s SCOT Business Intelligence team your work will have an immediate influence on day-to-day decision making at Amazon.com.

      As an Amazon Data Engineer you will be working in one of the world’s largest and most complex data warehouse environments. We maintain one of the largest data marts in Amazon as well as work on Business Intelligence reporting and dashboarding solutions that are used by thousands of users world-wide. Our team is responsible for mission critical analytical reports and metrics that are viewed at the highest levels in the organization. We are also working on newer tools that help users discover data using visualization and Big Data technologies. You should have deep expertise in the design, creation, management, and business use of extremely large datasets. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and to build data sets that answer those questions. You should be expert at designing, implementing, and operating stable, scalable, low cost solutions to flow data from production systems into the data warehouse and into end-user facing applications. You should be able to work with business customers in a fast paced environment understanding the business requirements and implementing reporting solutions. Above all you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive change.

      This opportunity is perfect for highly motivated and talented data engineers who want to apply and grow their technical depth and breadth while defining and driving key aspects of the customer experience on Amazon.com.

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      Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.

      Basic Qualifications

      • Degree in Computer Science or related field
      • Proficient with processing data on relational databases like Oracle/SQL Server/ Redshift/Tera data
      • Experience handling large data sets using SQL and databases in a business environment
      • Familiar with ETL and DW processes
      • Excellent verbal and written communication
      • Strong troubleshooting and problem solving skills
      • Thrive in a fast-paced, innovative environment

      Preferred Qualifications

      • Knowledge in using OLAP technologies and BI Analytics.
      • Oracle, Redshift, Linux, OBIEE experience
      • Experience with multiple database platforms
      • Familiar with computer science fundamentals including object-oriented design, data structures, algorithm design, problem solving, and complexity analysis

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