I built a free, interactive SQL practice tool for data engineering interviews
Most data engineering interview prep resources I found online were static — a list of questions with answers underneath. You read the answer, nod, a…
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ClickHouse 26.8 LTS: 57 Breaking Changes Since 26.3
If you run ClickHouse in production, you're probably on 26.3 LTS. And now 26.8 LTS has been announced, which means the LTS-to-LTS upgrade conversati…
SQL Execution Order Internals: Why WHERE Fails on Aliases but ORDER BY Succeeds
Ever wondered why this query fails in SQL? SELECT department_id , COUNT ( * ) AS emp_count FROM employees WHERE emp_count > 5 -- ❌ Error: Invalid…
AI-Driven Dynamic Pricing in Hotels: A Data Engineer's Deep Dive
I've spent the better part of a decade building data systems that power pricing decisions in the travel industry, and I can tell you this: dynamic p…
Building a Data Trust Score Engine on Google Cloud with BigQuery, Data Catalog & Vertex AI
Data has become one of the most valuable assets for modern enterprises, powering everything from business intelligence dashboards to machine learnin…
My First week in data Engineering:Setting Up My tools
This marked the beginning on an exiting journy .I started exploring Data Engineering. My firt focus was tool getting familiar with the required tool…
My First GitHub Project: From a Local Folder to GitHub Using Git and SSH
⭐🚀⭐🚀 When I first walked through the gates of LuxDevHq, my first thought was "endless possibilities". However, I was intimidated. I did not think I…
My First GitHub Project: From a Local Folder to GitHub Using Git and SSH
I thought that when i join Lux Dev i would jump straight into building complex data pipelines and getting to understand kafka, kafka sounds like a r…
Can We Stop Running Recurring Analysis as a Scheduled LLM Prompt?
Every major assistant now ships some version of scheduled prompts. You write "every Monday at 9am, analyze last week's signup funnel and tell me wha…
My Data Pipeline Caught an AI Fabricating a Source. Here's What 19 Years of Safaricom's Financial Data Taught Me About Trust.
Partway through building a data pipeline on Safaricom's public financial disclosures, one of my own extraction passes handed me two numbers for Ethi…
Five SQL Bugs That Never Threw an Error
A week cleaning 290 booking records taught me more about silent failure than any error message ever has Last week I cleaned a deliberately messy dat…
"Power Query Error: Formula.Firewall and Privacy Level Errors"
This isn't a syntax error or a bug in the query — it's Power Query's Formula Firewall refusing to combine data from more than one source until it kn…
Microsoft Fabric Now Encrypts Spark Temporary Data with Customer-Managed Keys;What It Actually Means
Microsoft Fabric has extended customer-managed key (CMK) encryption to cover temporary data generated during Spark job execution. This is not a mino…
The IR Is a sqlglot AST
Every data tool has an intermediate representation, whether it admits to one or not. It is the thing a model becomes after parsing and before execut…
interlace.sh: Why We Built a Unified Abstraction
Consider what a data engineer has to learn before writing a single useful transformation on a typical 2026 data stack. dbt, for SQL models, sources,…
The One-Minute Trap: What Microsoft Fabric's New Warehouse Billing Model Means for Your Workloads By Gilbert Kiptoo Lelon | DP-700|DP-600
Microsoft is changing how Fabric Data Warehouse charges for compute starting August 2026. Most teams will discover what that means on their next cap…
Keeping Your Own Files Straight
A migration produces hundreds of files: extracts, load files, rejected rows, mapping versions, exception lists. Losing track of which sheet is curre…
Stage 3: Map the Fields
The field map is a line by line list saying what each field in the old system becomes in the new one. It is the blueprint for the entire job, it is…
The Emails That Keep a Migration Moving
Most of a migration is run by email, and four of them do almost all the work. Each one carries the same four parts, and the parts are the reason the…
Stage 5: The Dry Run
The dry run is a full load into a sandbox, followed by reconciliation. It is the stage the research is loudest about, and it is the one that decides…
Stage 7: Freeze, Cutover, Bridge
Cutover is the switch from old system to new. The part most write-ups skip is the gap: a migration takes weeks, and the business does not stop while…
Your AI did not change the metric. Your business did.
Ask an AI assistant for MRR today and again next quarter. The SQL can be valid both times while the answers use different definitions. Finance may h…
Reflecting on 7-8 Years of Career Growth: Adaptability and Continuous Learning Key to Senior Data Engineer Success
Analytical Insights: The Mechanisms Driving Career Growth in Data Engineering In the rapidly evolving field of data engineering, career progression…
The Airbyte Column Nobody Queries: Find Every Silent Sync Failure in 15 Minutes
You added a new field to your CRM. Three weeks later, someone in finance asks why 4% of deal values in the warehouse are NULL when the CRM UI clearl…
zhao-dbt-plan: a microbatch cascading time-window planner for dbt
A few days ago I posted about zhao-cli , a breaking-change gate for dbt (link at the bottom if you missed it). This is the second tool in the same f…
Stage 4: Clean and De-dupe
Cleaning is where you fix what can be fixed automatically and escalate everything else to the client. The output is a source that the target system…
Medallion architecture on Databricks: what actually matters
Every Databricks pitch deck has the same three-layer diagram: bronze for raw data, silver for cleaned data, gold for business-ready tables. The diag…
Your Extraction Pipeline Doesn't Need a Smarter Model. It Needs a Schema Contract Test.
Last quarter I inherited a small pipeline that does something increasingly common: pull unstructured text (vendor emails, PDF invoices, changelog en…
You Review AI Code Less Carefully Than Human Code. That Is Backwards.
Two pull requests land. A colleague wrote one by hand, and you read every line. The other came out of an AI tool, and it looks clean, consistent, an…
dbt Semantic Layer vs Cube vs AtScale: Choosing an Enterprise Semantic Layer
Three semantic layers, three architectures, three very different bills. All three will define what a metric means. None of them proves an AI agent i…