Senior Data Engineer
amazon
Luxembourg, LU
il y a 3j
  • Flexibility for alternate EU Amazon offices*
  • Amazon’s mission is to be the most customer centric company in the world. The Workforce Staffing organization is on the front line of that mission by hiring the hourly fulfilment associates who make that mission a reality.

    To drive the necessary growth and continued scale of Amazon’s associate needs within a constrained employment environment, Amazon is creating a Workforce Staffing Analytics program.

    This program will re-invent how Amazon attracts, communicates with, and ultimately hires its hourly associates. This team will own multi-layered research and program implementation to drive deep learnings, process improvements, and strategic recommendations to global leadership.

    Are you passionate about data? Are you a tinkerer by trade? Do you enjoy questioning the status quo? Do complex and difficult challenges excite you?

    If yes, this may be the team for you.

    As a Senior Data Engineer, you will provide technical leadership, lead data engineering initiatives and build end-to-end analytical solutions that are highly available, scalable, stable, secure, and cost-effective.

    You strive for simplicity, demonstrate creativity and sound judgement. You deliver data solutions that are customer focused, easy to consume and create business impact.

    You are passionate about working with huge datasets and have experience with the organization and curation of data for analytics.

    You have a strategic and long term view on architecting advanced data eco systems. You are experienced in building efficient and scalable data services and have the ability to integrate data systems with AWS tools and services to support a variety of customer use cases / applications.

    In this role, you have the opportunity to :

  • Design, implement and operate large-scale, high-volume, high-performance data structures for analytics and data science.
  • Implement data ingestion routines both real time and batch using best practices in data modeling, ETL / ELT processes by leveraging AWS technologies and big data tools.
  • Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
  • Collaborate with engineers to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation.
  • Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers.
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