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Senior Business Intelligence Engineer (m/f)

  • Luksemburg
  • Specjalista
  • 2017-09-27

    Pracodawca ma prawo zakończyć rekrutację we wcześniejszym terminie.


    Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decision based on your experience and skills. We value your passion to discover, invent, simplify and build. We welcome applications from all members of society irrespective of age, sex, disability, sexual orientation, race, religion or belief.

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    Senior Business Intelligence Engineer (m/f)
    Amazon is looking for an outstanding Business Intelligence Engineer to join the Amazon Customer Fulfillment Finance BI team.

    We are looking for someone striving to make a difference in how we store and retrieve data sets, and build scalable systems able to cope with vast amounts of data. For that, we need exceptional people with outstanding ETL skills and a good understanding of data flows, to guide our BI team by being a specialist and contact for all ETL questions.

    Basic qualifications:

    • 6+ years of experience creating ETL solutions
    • Degree in a technical field (Computer Science, Information Management, Mathematics, Business Informatics)
    • Advanced analytical skills and strong detail-orientation
    • Working knowledge of DBA best practices (e.g., schema management, index optimization, OS-level tuning, Network management, etc.)
    • Query and database tuning skills
    • Working knowledge of a scripting language e.g. Python, Ruby, Perl

    Preferred qualifications:
    • Familiarity with AWS (EC2, Redshift)
    • Familiarity with Microsoft SQL Server


    Main responsibilities will include:

    • Working with internal customers to understand their needs and design, review and implement schema designs to meet those needs
    • Creating ETL solutions with a focus on ensuring data quality
    • Work closely with BI engineers to ensure that our BI tools and databases work together efficiently
    • Continuously innovate to optimize data flows and models, to deal with increasing amounts of data and rapidly changing requirements