37 stories tagged with #dataengineering, in publish-time order across the WeSearch catalog. Tag pages update as new stories ingest.
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# Modernizing the Pitch: Building an Automated SQL Data Quality and Transformation Pipeline for Multi-Club Scouting Platforms
In global football administration, data is the ultimate competitive edge. Multi-club organizations...…
Your AI Agent Is Failing Because of Your Data Layer, Not Your Model
Here's a pattern I keep seeing: a team builds an AI agent, the demo works, they ship it, and within a...…
Three Ways to Set Up CDC from Postgres to ClickHouse
Postgres CDC into ClickHouse via Kafka + Debezium, MaterializedPostgreSQL, and ClickPipes — setup, schemas, monitoring SQL, and where each one breaks.…
HTTP 200 Is a Lie: A 30-Line Schema Canary for Source Drift
A scraper that returns HTTP 200 is not a scraper that returns good data. Those are two different...…
One Practical SQL Trigger Example You Can Actually Use
One UPDATE statement. One trigger. One automatic audit record — no extra code required. Triggers are...…
How AI Is Reshaping the Data Engineer Role in 2026
What Changed in Data Engineer Job Descriptions Around 2023? For years, a Data Engineer job...…
Building the Pipes: Core Data Engineering Concepts Explained
Introduction Data engineering is the practice of designing and building systems for...…
Data Normalization Across Dublin Rental Portals: How to Make Listings Comparable
Data Normalization Across Dublin Rental Portals: How to Make Listings Comparable Dublin...…
Capacity Governance in Microsoft Fabric: The Layer Most Teams Forget
More and more organizations are moving to Microsoft Fabric to bring all their analytics into one...…
How Polymarket Scaled Their Data Stack with Postgres + ClickHouse
Prediction markets move fast — and so does their data. As Polymarket grew to billions in monthly...…
Chronos vs Toto: Zero-Shot Forecasting Benchmark Results
Introduction Good forecasts help with capacity planning and quieter alerts. But one...…
Copy Job CDC with SQL estate is now GA in Microsoft Fabric
Microsoft Fabric Copy Job CDC with SQL estate is now generally available. Here is what BI and data engineering teams can actually do with it.…
Replicate MySQL to ClickHouse with Sling
Introduction ClickHouse is a columnar OLAP database. It runs aggregate queries across...…
How to analyze the cost of Kafka?
Which side are you on: "This is just what Kafka costs at scale" or "We should switch to a cheaper...…
From Python to Production Pipeline :A Practical guide to Apache Airflow
You have been using python and you have written scripts that pull data, clean it and load it...…
Deeper into Dataform 1: Exploring the API
Series overview This series of blog posts is aimed at Dataform users who are looking to...…
Building a Real-Time Kafka + Cassandra Pipeline
Introduction Apache Kafka and Apache Cassandra pair effectively because they complement...…
A Beginners guide to Real-time Data Streaming with Apache Kafka
Introduction Ever wondered how banks are able to detect and stop fraud in real-time? This...…
FSx for ONTAP S3 Access Points Lakehouse — What Works, What Doesn't, and Why
TL;DR Amazon FSx for ONTAP S3 Access Points let you access NAS file data through...…
Single-Node Data Engineering: DuckDB, DataFusion, Polars, and LakeSail
For the past decade, data engineering was synonymous with distributed clusters. If your dataset...…
An In-Depth Overview of the Apache Iceberg 1.11.0 Release
Apache Iceberg 1.11.0 was officially released on May 19, 2026, marking a major milestone in the...…
Google Maps Scraper: Build Local Data Pipelines That Actually Run
You do not need another CSV export that works once and quietly dies three days later. A Google Maps...…
Approaches to Streaming Data into Apache Iceberg Tables
This is Part 13 of a 15-part Apache Iceberg Masterclass. Part 12 covered Python and MPP engines. This...…
Apache Iceberg Metadata Tables: Querying the Internals
This is Part 11 of a 15-part Apache Iceberg Masterclass. Part 10 covered maintenance operations. This...…
Treasure Hunt Engine Was a Disaster Waiting to Happen: A Tale of Unchecked Growth and Overlooked Trade-Offs
The Problem We Were Actually Solving At the time, we were facing the classic scaling...…
Category: Events
The Problem We Were Actually Solving Behind the scenes, this application relies on a...…
Building A Cross-Border E-commerce System That Just Works
The Problem We Were Actually Solving As a data engineer, I was tasked with designing a...…
Data Infrastructure in a Digital Exile
The Problem We Were Actually Solving As a data engineer, I've spent years building data...…
Beyond the Stateless Prompt: Building an Auditable Product Intelligence Pipeline with Cascadeflow and Hindsight
Pasting a 10,000-line CSV of customer support reviews into a stateless LLM context window is lazy...…
Headless BI: How a Universal Semantic Layer Replaces Tool-Specific Models
Your organization uses Tableau for executive dashboards, Power BI for operational reports, and...…
The Fallacy of Digital Platforms: Why Stripe Isn't Always King
The Problem We Were Actually Solving Our primary goal was to create a seamless purchasing...…
Why Stripe Didnt Cut It for Creators in Pakistan — and How We Built a Parallel Pipeline for $0.05 Per Transaction
The Problem We Were Actually Solving Our creators in Lahore, Karachi, and Islamabad needed...…
Selling Digital Products Without Platforms' Arbitrary Approval
The Problem We Were Actually Solving Our team focused on creating an inclusive marketplace...…
The Feature Store: Consistency and Latency Are Both Non-Negotiable
Part 3 of 5 in the series: When Your AI Pipeline Grows Up In the previous post, we worked through...…
What I Learned From Reading 50 Data Pipeline Postmortems
After analyzing 50 public postmortems from Uber, Netflix, Stripe, and others, four failure patterns...…
🧞♂️Transform unstructured PDFs Job Offers into a dataset w. gemma4:2b
This is a submission for the Gemma 4 Challenge: Build with Gemma 4 🤔 About the power of...…
The Missing Organizing Principle of Microsoft Fabric: Medallion Architecture Explained :gem:
If you've tried picking up Microsoft Lakehouse, Synapse Spark, Data Factory, and Power BI recently,...…