Senior Data Engineer, Global Procurement Technology

hace 4 semanas


Madrid, Madrid, España Amazon A tiempo completo

We are seeking a talented and inventive engineer who insists on the highest standards, with a strong passion for modern data technologies and an interest in improving business processes by building solutions to extract valuable insights from the data.

The Global Procurement Technology team, as a fundamental pillar of Global Procurement Operations, is looking for a skilled Data Engineer to lead related engineering activities and help build its future data ecosystem.

You will be a member of the Data Engineering Team, joining a fast-growing global organization with a vision to transform the Procurement field and become a solution leader in the market.

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

We support various initiatives, including but not limited to strategic supplier sourcing, contract management, spend analytics, order management, and supplier risk and performance analysis.

We are seeking an individual who can thrive in a fast-paced work environment, collaborating and sharing knowledge and experience with colleagues.

You will connect with world leaders in your field and tackle Data Engineering challenges to ensure business continuity and high-quality decision-making, working backwards with your customers.

Key Job Responsibilities
  • Lead the design and development of highly scalable and efficient database systems and pipelines, supporting process optimization in Procurement operations management, analytics, and reporting.
  • Lead data integration projects, acting as the proxy for other engineering senior leaders.
  • Be an expert in the architecture of data warehousing products, capable of utilizing various technologies and tools.
  • Have strong analytical skills and excel in the modeling, creation, management, and enterprise use of large data sets, combining raw (complex) data from different sources.
  • Define the best design and development practices to extract, transform, and load (ETL) data from various sources (internal or external), supporting the rapidly growing and dynamic demand for data; deliver data as a (self-)service, which will have an immediate influence on day-to-day business decision-making.
  • Be the Subject Matter Expert (SME) for any data solutions while striving for efficiency by aligning data product initiatives with business goals.
  • Organize related workshops and demos to share knowledge across teams and ensure that all data engineers follow similar design and development practices.
  • Cooperate with different groups of stakeholders, e.g., engineers, scientists, product/program managers, senior leadership, etc.


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