Archive - Data Gibberish

February 2025

Pass the Behaviour Interview or How to Stop Being A Hater

5 red flags you may need to work on. I’ve stopped interviews for the 10th minute because of #4.

Feb 26 •

PySpark Internals Explained: Essential Guide for New Data Engineers

Behind the scenes of PySpark: decode its architecture, learn how it handles transformations and actions, and optimise your workflows for high-speed data…

Feb 19 •

Essential Data Engineering Stakeholders: The Roles That Shape Your Work

Discover the important stakeholders data engineers engage with and why building strong relationships with them can shape your job.

Feb 11 •

Data Lakes For Complete Noobs: What They Are and Why The Hell You Need Them

Everybody around you and me talk about warehouses and lakehouses. Here’a why data lakes are not dead yet

Feb 5 •

Level-Up Data Engineering: Write Rock-Solid Python With Strict Typings

You are reading Level-Up Data Engineering — a special monthly minicourse series designed to turn mid-level data engineers into senior.

Feb 1 •

January 2025

How Data Engineers Use DeepSeek to Write High-Impact Documents Faster

Find out how generative AI can streamline workflows, cut manual effort, and boost the clarity of your documents

Jan 29 •

CSV vs. Parquet vs. AVRO: Pick the Optimal Format for Your Data Pipeline

Not all file formats are equal. Learn when to use CSV, Parquet, or AVRO for the best balance of performance, scalability, and storage efficiency.

Jan 22 •

Struggling with Keeping Database Environments in Sync? Here’s My Proven Fix

Are you stuck managing chaotic database environments? Discover how I implemented a proven, hassle-free approach to effortlessly sync dev and production…

Jan 15 •

Merge vs Rebase in Git: Data Engineer’s Guide to Choosing the Right Workflow

Learn the inner workings of merge and rebase in Git, uncover their key differences, and get actionable advice on when to use each.

Jan 8 •

Here are th most popular articles of 2025 you may have missed.

Jan 4 •

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