Data Engineer

Essential:

- Proficiency in R
-data manipulation using dplyr
-Functional programming using purrr
-Joins and relationship management
-Debugging pipelines

Git & GitHub
-Branching strategy
-Pull requests
-Merge conflicts resolution
-Release tags
-Code reviews

AWS or other cloud compute platforms
-S3/Data storage concepts
-Reading/writing from S3

Data Pipelines
-Inputs > Processing > Outputs

Data Engineering
-Checking lineage of columns/data sets

Statistical/Modelling Concepts

QA -Unit testing
-Reconciliation checks
-Regression testing