Data Engineer, Global Procurement Technology
Luxembourg, LUX
il y a 5j

Job summary

Are you a talented and inventive engineer with a strong passion about modern data technologies and interested to improve business processes, extracting value from the data?

The Global Procurement Technology is looking for a Data Engineer to help build its future data ecosystem. You will be a member of the Data Engineering and Science Team, joining a fast-growing global organization, with a great vision to transform the Procurement field, and become the role model in the market.

This team plays a strategic role supporting the core Procurement business domains as well as it is the cornerstone of any transformation and innovation initiative.

Our mission is to provide a high-quality data environment to facilitate process optimization and business digitalization, on a global scale.

We are supporting business initiatives, including but not limited to, strategic supplier sourcing (e.g. contracting, negotiation, spend analysis, market research, etc.

order management, supplier performance, etc. You will connect with world leaders in your field and you will be tackling Data Engineering challenges to ensure business continuity, by taking the right decisions for your customers.

Key job responsibilities

As a Data Engineer in the team, you will :

  • design, develop and enhance data systems and pipelines, supporting process optimization in reporting, planning, and analytics
  • integrate in-house data services with partners' systems
  • drive the development of data warehousing solutions, using various technologies and tools
  • have strong analytical skills and excel in the design, creation, management, and enterprise use of large data sets, combining raw data from different sources
  • be responsible for the design and implementation of scalable extract, transform, and load (ETL) processes to support the rapidly growing and dynamic demand for data;
  • deliver data as a service, which will have an immediate influence on day-to-day business decision making

  • prepare operational data to automate data integrity and activity monitoring
  • cooperate with different groups of stakeholders, like engineers, scientists, product / program managers, etc. to evaluate business needs and objectives, and provide the best data management environment
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