Data engineer should have at least 2 years of relevant AWS experience with their services mentioned below. For senior data engineer the person should have at least 3 to 4 years of experience on the tools
Primary focus is on Glue, S3, Redshift, Lambda, PySpark, Spark with added advantage in AWS Step function, NoSQL DB like Dynamo DB and AWS Data Migration Service in that order of priority.
Secondary focus is on cataloguing (using collibra), workflow, lineage harvester.
Experience in data security or governance and performance improvement is an added benefit
Only focus is on AWS services and tech stack. Other big data platforms wont add much value for the candidate in their client interview
Looking for logical reason behind the choices made by candidate for their coding practices. It can be anything where the coder chooses a tool over the other or what are the best practices the person is using or what are the problems the coder faces when using 2 components together like Redshift with S3, etc.