Data Engineer

 
Data Engineer will be mainly building APIs, securing them efficiently, and building ETL pipelines. This involves grabbing data from other systems, maybe external vendor API, doing some business accessing and pushing data to data lake in AWS, and building ETL pipelines.)
You will be responsible for building the solution as to how data is more accessible (for the portfolio mgrs.)

Must Haves:
·        5 years +.
·        Building APIs, hands on! They build in python and pyspark.
·        Understanding the security components of securing the APIs (making sure the data isn’t available to everyone) (grabbing data from other systems, maybe external vendor API, doing some bizz accessing and pushing data to data lake in AWS. Another angle- building pipelines ETL.)
·        Graph QL – how do you use it?
·        Aws – pyspark.
·        AWS: Athena, S3, Glue, EKS – ask what they have used and how
·        Need to be adaptable to changes and the potential to switch frameworks/languages/projects.


BIG Plusses: ( please include in SS Boolean)
·        Finserv BG preferred.
·        Graph QL: big plus

Day-to-day:
·        Small team. 5 other DEs.
·        Scrum mtgs daily, weekly deliverables
·        project they’re building: 3 mo down the lin,e might scrape it and do something else. Adaptable mindset

Summary:
·        making data more accessible for the portfolio managers and investors.