• Extensive and proven technical background in data warehousing with a good understanding of its core elements such as data ingestion, data unification/modeling and data consumption as well interest in elements related to data governance such as data quality, data lineage and metadata management.

• The ability to identify structural and preferably automated solutions to common technical challenges by taking the lead in drafting designs, refining the workload and guiding the implementation towards production together with an agile squad of devops engineers with a balance of junior, medior and senior profiles.

• The ability and the ambition to continously learn new (open source) tools and technologies that will be part of our new platform such as Hive, Spark, HDFS and Ni Fi in order to assist with the gradual but steady migration of flows from the current data warehousing stack towards the new big data platform as well as assisting with new functionality such as streaming data ingestion, spark job execution and open metadata (Egeria) standards.

• Tech stack/ knowledge:
  • Mandatory:

• Experience with ETL processes and tools, IBM Infosphere Data Stage preferably
• Experience with Hadoop technologies (Hive, Spark, HDFS and Ni Fi)
• Experience with Shell scripting
• Good knowledge of Hive, Impala and Oracle Database (database design, database optimizations and data analysis on large amounts of data)
• Ability to translate functional and non-functional requirements (e.g. Security, High Availability)\

• • Nice to have:

• You see benefits with pair programming
• Understanding of Agile - Scrum methodology is considered a plus