Before starting chasing analytics and data engineering jobs I usually suggest to be more or less fluent with multiple things:

- CLI: popular commands, navigation, vim and nano text editors, permissions, environment variables
- GitHub (or any similar platform) with focus on Code Reviews, PRs, development lifecycle, basic pre-commit, CI/CD
- Containers: docker file, image, compose
- IDE of your choice: don't know where to start? Take Visual Code.

You don't need to be pro in any of these but it will make a difference and pay back in long term i.e. #engineeringexcellence

Last week at Surfalytics I ran CLI and GitHub and next Saturday planning to wrap containers.

All of this will wrap into the 3 simple free courses - "Just enough <TERM> for data professional"

Link for like: https://www.linkedin.com/posts/dmitryanoshin_engineeringexcellence-dataengineering-analyticsengineering-activity-7138073576309489667-_H2h