Reliable Data Engineering

Technology EN ↓ 6 episodes

Discover how to build, deploy, and maintain data pipelines that scale reliably in production. This podcast features practical lessons on Databricks migrations, dbt best practices, SQL optimization, cost reduction on cloud platforms, and data quality frameworks—all designed to help data engineers avoid costly mistakes.

Author

Reliable Data Engineering

Episodes

Data Engineering Is Not One Job Anymore 11.01.2026 4:05

Ten years ago, being a generalist worked. In 2026, companies don't hire "tool collectors." They hire specialists who solve specific problems exceptionally well. Here's which path pay and which leaves you unemployable.

dbt Is Not an ETL Tool — And That’s Okay 08.01.2026 4:50

dbt is often treated like a full ETL platform — and that expectation causes more problems than it solves. In this episode, we break down what dbt was actually designed for, where it shines, where it doesn’t, and why accepting its limits leads to cleaner pipelines and better data architecture.

Comparing Databricks, Snowflake, and BigQuery: Same Query, Real Costs 08.01.2026 6:13

A side-by-side analysis of query performance, pricing, and operational differences across three leading data platforms

I Replaced My Databricks Pipeline with AI Agents — Here’s What Actually Happened 08.01.2026 4:08

A story about how AI agents what do for us!

How AI Will Transform Data Engineering in 2026 03.01.2026 11:48

A realistic look at what’s coming and the skills that will keep you ahead of the curve

Welcome to Reliable Data Engineering - Here's What You'll Learn 03.01.2026 1:01

Welcome to Reliable Data Engineering—the podcast for data engineers who build production systems and want to stay ahead of the curve. I'm your host, a data engineer with 6+ years building enterprise-scale data infrastructure. I've migrated 500+ dbt models to Databricks, optimized SQL workloads across multiple platforms, and managed complex data governance at scale. Now I'm sharing the...