Senior Data Engineer, Global Procurement Technology

- Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Experience building data products incrementally and integrating and managing data sets from multiple sources
- Experience communicating with users, other technical teams, and management to collect requirements, describe data modeling decisions and data engineering strategy
- Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with MPP databases such as Amazon Redshift
- Experience operating large data warehouses
- Experience providing technical leadership and mentoring other engineers for best practices on data engineering

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
Are you a talented and inventive engineer, who insists on the highest standards, with a strong passion about modern data technologies and interested in improving business processes building up solutions to extract valuable insights from the data?

The Global Procurement Technology, 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, becoming a solution leader in the market as well. 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 various initiatives, including but not limited to strategic supplier sourcing, contract management, spend analytics, order management, supplier risk and performance analysis, etc.

We are seeking an individual who can thrive in a fast-paced work environment, be collaborative sharing knowledge and experience with his colleagues. In Amazon, you will find a number of resources available to learn new skills and develop your career. You will connect with world leaders in your field and you will be tackling Data Engineering challenges to ensure business continuity and high-quality decision making, working backwards with your customers.

Key job responsibilities
As a Senior Data Engineer in the team, you will:
- 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, being 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. to evaluate properly any requirements or dependences to recommend optimal solutions to the problems