What Tools should Data Engineers know in 2025 | 25+ Best and Worst Tech Stack Ranked

Feeling overwhelmed by the endless tools in Data Engineering? 🤯 Not all tools are worth your time, and some are already obsolete! In this video, I rank the top Data Engineering tools across five levels based on learning effort and industry usage. 🚀 📌 We'll cover: ✅ Must-learn tools (Green Zone) ✅ Trending tools across job roles (Blue Zone) ✅ High effort but necessary tools ✅ Low effort, widely used tools ✅ Dead tools you can skip From Python, SQL, and Excel to Spark, Airflow, Kafka, Snowflake, and beyond, I’ll break down which tools to focus on in 2025 and beyond! 🔑 TIMESTAMPS ============== 0:00 - 01:26 - Intro 1:26 - 03:48 - Prereqs 03:48 - 05:55 - Data Eng tools 05:55 - 07:18 - Data Processing tools 07:18 - 08:59 - ETL/ELT tools 09:00 - 11:51 - DataWarehouse/Data Lakehouse 11:52 - 13:05 - DevOps tools 13:05 - 14:03 - Learning Strategy 14:03 - 14:27 - Conclusion ✨ Subscribe for more videos on data, AI, and productivity! ============== 🌱Let's chat LinkedIn : / https://www.linkedin.com/in/sunjana-ramana/ ============== 🔗 FREE Resources: Sign Up For Notion : https://bit.ly/4hnVExY Notion Template : https://bit.ly/3E2vbr8 Search API : https://www.searchapi.io/?via=src ==============