Data Engineer

Description

Business area: this team supports the Common Data Layer (CDL) for E2E supply chain data across plan, source, make, deliver. This is essentially a large data lake of curated data that is used by supply chain business partners. The team created multiple data models/assets that are reused by the business.
Must have experience with LARGE data sets - billions of records
must have experience with data automation
Must have thought leadership and be able to think creatively and differently
Must have a data engineering background (NOT data modeling)
Strong with SQL and Python
Team uses a low/no-code drag and drop ETL tool called "prophecy". They do not need to have experience with this tool, but should have strong foundational knowledge with ETL/data engineering.
Dan will give them 90 days with clear direction on deliverables to see what they come up with. If the resource does well, he will be able to pull funding from the existing team to extend them
Goal is to start to right size the team - by bringing in this senior person to automate processes, he will be able to offboard some of the existing manual ETL engineers.
Challenge: they are not getting the return on their investment anymore - the existing team are data modelers who do NOT have the data engineering background and therefore can't think outside the box