Can’t-Ignore Data Engineering Advancement Habits
Habits for data engineering job seekers, entry-level engineers and veterans looking to level-up.
Habits for data engineering job seekers, entry-level engineers and veterans looking to level-up.
Categorizing data engineering IDEs to facilitate professional, production-adjacent development.
Constrained by the limitations of my credit card’s pre-filtered dashboards, I used Python, SQL & Looker to create my own.
How data engineers can wield the power of the “brag sheet” to achieve career-altering results.
4 unconventional but useful data engineering applications I built that saved me at least 50 hours of work and personal time.
Solve a real-life SQL array problem in an easy-to-follow walkthrough.
1 undervalued data engineering skill that, if left unrefined, could cost you or your org millions of dollars.
4 thankless tasks effective data engineers must do — especially before Q4 and the holiday season.
Building time-sensitive data pipelines is a challenge; luckily, there is a way to build localized pipelines with 3 lines of Python.
Avoid GCP 401 errors — and security concerns — by passing project credentials into your Docker image the right way.
Leverage the Python Google Cloud Storage and BigQuery APIs to bulk download, transform and upload CSV files in < 1 minute.
Either afraid or stuck in old habits, new engineers fail to ask important probing questions; how devs can think critically.