SQL

The Guerrilla Guide to Data Engineering Interviews

The Scenario That Changes Everything Picture this: You’re sitting in an interview room—or more likely these days, staring at a Zoom window with your carefully curated bookshelf background—and the interviewer asks you about data quality. “Tell me about your experience with data quality,” they say. You have two choices. Choice A: “Data quality is really important in data engineering. It involves ensuring data is accurate, complete, consistent, and timely. I believe strongly in implementing data quality checks throughout the pipeline.”

Sunday, January 11, 2026 Read

When Your Data Quality Fails at 9 PM on a Friday

When everything goes wrong at once It’s 9 PM on a Friday. You’re halfway through your second beer, finally relaxing after a brutal week. Your phone buzzes. Then it buzzes again. And again. The support team’s in full panic mode, your manager’s calling, and somewhere in Melbourne, two very angry guests are standing outside the same Airbnb property—both holding confirmation emails that say the place is theirs for the weekend.

Saturday, November 22, 2025 Read

dbt Fusion: The Engine Upgrade That's Got Everyone Talking

When Your Favorite Tool Gets a Makeover You know that feeling when your favorite app suddenly changes its interface? That mix of excitement and anxiety about whether the changes will actually improve your workflow or just mess with muscle memory you’ve spent years building. That’s exactly what happened when dbt Labs dropped dbt Fusion on the analytics engineering community. The reactions were… let’s call them passionate. Some folks were celebrating like they’d just discovered fire, while others were questioning whether this marked the beginning of the end for open-source dbt.

Saturday, June 21, 2025 Read

Mastering Data Interviews: A Comprehensive Guide

Introduction After nearly two decades in the data engineering field, I’ve sat on both sides of the interview table countless times. Whether you’re a seasoned professional looking to change roles or a newcomer trying to break into the field, the interview process for data engineering positions can be both challenging and mysterious. There’s often uncertainty about what questions you’ll face, what skills you need to demonstrate, and what interviewers are really looking for beneath the surface.

Saturday, February 22, 2025 Read

Data Modeling Showdown: Kimball vs One Big Table vs Relational

Introduction When architecting a data warehouse, one of the most crucial decisions is choosing the right data modeling approach. Like selecting the right tool for a job, each modeling methodology has its strengths and ideal use cases. Today, we’ll explore three popular approaches: Kimball’s dimensional modeling (star schema), the one big table approach, and traditional relational modeling. The Dataset: Understanding Our Example To illustrate these approaches, let’s consider a retail sales system with these core components:

Saturday, January 25, 2025 Read

Data Industry Trends: What to Expect in 2025

Introduction The data industry has kicked off 2025 with transformative developments that are fundamentally reshaping our approach to data management and analytics. The landscape is witnessing seismic shifts - from Databricks’ historic funding round to Boomi’s strategic acquisition of Rivery, and the industry-shaking Iceberg buyout. Yet amid this technological evolution, a critical question emerges: how will these advancements translate into tangible value for organizations? As we navigate through this dynamic environment, the focus extends beyond identifying dominant technologies to understanding their practical impact on business outcomes. Let’s explore the key trends that are defining the data world in 2025, and more importantly, how they’re reshaping the way organizations leverage their data assets.

Saturday, January 18, 2025 Read