DevOps at ING Analytics: combining data engineering with data operations
ING was one of the early adopters of the DevOps movement. Currently, there is a lot of expertise in the organization: way of working, tools, and HR are all catered for DevOps. In the Analytics area, these best practices were the basis of a modern and stable architecture where data engineers, operations, and data scientists work together with business people on daily basis. The technology stack includes Hadoop, Spark, Flink, Kafka, Cassandra, and several IBM tools. In the talk I’m going to share tools evolution, skills and processes in place. Touching in the second part two use-cases.
Giuseppe is a Senior Data Engineer at ING, working in the Analytics department. After completing a master in Computer Engineering, he joined ING Group in 2014, where he worked on several international projects in data analytics and security. With his academic background in Artificial Intelligence, Pattern Recognition and Software Development and his big passion for data analytics, the Fast Data field has been a perfect match. He now works in the Fast Data team on streaming applications that make the customer communication extremely personalized and relevant.