📰 Medium · DevOps

Escape Deployment Fatigue from Frequent Schema Change Continue reading on Snowflake Builders Blog: Data Engineers, App Developers, AI, & Data Science »

The puzzle A classic trick question: how many times does the digit 9 appear between 1 and 100? Continue reading on Medium »

Part 5 of the “The Data Engineering Stack” series. You wanted to schedule three jobs. You ended up maintaining a distributed system. Continue reading on Medium

It would have been faster to build this as one FastAPI app. Fetch news and weather, write it to a database, render a dashboard, done… Continue reading on CodeTo

I am not one who writes many love letters. But once in a while, when you don’t expect it, good things come along and they take a little… Continue reading on Sno

Ask most engineering teams whether their service is reliable enough, and you’ll get a nod, instead of numbers. Dashboards are green… Continue reading on KloudMa

Are you still relying on manual SQL scripts for your database deployments? In this video, I break down how to implement Liquibase to treat… Continue reading on

Whether you’re deploying a new application, refreshing a database environment, or setting up a new schema, you’ll inevitably face the task… Continue reading on

Apache Iceberg gives you ACID semantics, schema evolution, partition evolution, and time travel on object storage. What it does not give… Continue reading on IT

How to Choose Between File, Object and Block Storage Continue reading on Medium »

# From SQL to Snowflake Cortex AI: The Complete Roadmap to Becoming a Modern Data Engineer in 2026 Continue reading on Medium »

When I first started studying data engineering, I believed the job mainly involved writing SQL queries and building ETL pipelines… Continue reading on Medium »

Picture this: it’s 4:30 PM on a Friday. Someone just ran a rogue SQL script directly in production, and the dashboards your executives… Continue reading on Medi

As organizations increasingly rely on data to make informed decisions, the demand for skilled data professionals continues to grow. Two… Continue reading on Med

If you work in Data Engineering then your codebase is likely a chaotic cocktail of Python (for Airflow, Prefect or PySpark), massive… Continue reading on Medium

By almost every count on the board, your team is thriving. Continue reading on Medium »

Evolution of Infrastructure Intelligence. Continue reading on Medium »

One Data Structure That Can Cut Database Traffic by 90% Continue reading on Medium »

Just like on a rink, two developers enter the shared BI app to compete for the same measure. Only one will survive. By morning there’s a… Continue reading on Me

A follow-up to the Windows Event Logs → Kafka series — this time, we ditch the connector and go full OTel. Continue reading on Medium »

Welcome to the Spark 4 Freak Show — the only carnival where defaults bite, configs whisper from the walls, and the architecture finally… Continue reading on Tow

3–5 sets (or more) of SQL alert queries are needed to write for each Databricks table we are managing, and we have 1000+ tables in our… Continue reading on Medi

Built for Lakerunner, the lakehouse engine behind Cardinal⁠. Measured against Parquet + DuckDB and Vortex on 1.46M real log rows. Continue reading on Medium »

If someone had told me a few years ago that I’d be learning Python, analyzing datasets, and interviewing for Business Intelligence Analyst… Continue reading on