Uploaded November 2022 | Updated September 2026, 2 weeks ago
Tommy Dang is the Co-founder and CEO of Mage, building a data ingestion and transformation pipelines tool for DE (github.com/mage-ai/mage-ai). Previously, he was working on data engineering and machine learning engineering at Airbnb. He has a bachelor degree of science in UC Berkeley studying economic, history, sociology. Today we’ll talk about how he learned engineering and machine learning after college, data tools and ML tools he built at Airbnb, performance review, and how he navigates his career. If you like the show subscribe to the channel and give us a 5-star review. Subscribe to Daliana's newsletter on dalianaliu.com for more on data science and career.
Tommy’s LinkedIn: linkedin.com/in/dangtommy
Daliana's LinkedIn: linkedin.com/in/dalianaliu
Daliana's Twitter: twitter.com/DalianaLiu
00:00:00 Introduction
00:01:28 Get into computer science from non-tech background
00:03:08 How he started his first project
00:04:07 Projects at Airbnb
00:06:09 Speed vs Quality when building data pipelines
00:16:34 How to deal with AdHoc requests
00:21:00 How did he learn machine learning
00:24:04 How he convinced data scientists to teach him ML
00:25:15 Performance review
00:27:11 Don’t let your job title limit your career
00:28:29 Why he started his company
00:31:38 Build your own tool vs use open source solutions
00:33:12 Transitioning from an engineer to a CEO
00:34:50 Earn trust from internal stakeholders
00:36:27 Career advice
00:41:31 How he carved his own path at Airbnb
00:46:00 How did he learn to be a good engineer
00:47:10 Best advice for data scientists or engineers
00:48:41 Most important quality of data scientists or engineers
00:51:51 Design principles
00:58:51 Future of tools
01:01:00 What does he think about his future career
01:05:05 Inspiration of Tommy
Tommy Dang is the Co-founder and CEO of Mage, building a data ingestion and transformation pipelines tool for DE (github.com/mage-ai/mage-ai). Previously, he was working on data engineering and machine learning engineering at Airbnb. He has a bachelor degree of science in UC Berkeley studying economic, history, sociology. Today we’ll talk about how he learned engineering and machine learning after college, data tools and ML tools he built at Airbnb, performance review, and how he navigates his career. If you like the show subscribe to the channel and give us a 5-star review. Subscribe to Daliana's newsletter on dalianaliu.com for more on data science and career.
Tommy’s LinkedIn: linkedin.com/in/dangtommy
Daliana's LinkedIn: linkedin.com/in/dalianaliu
Daliana's Twitter: twitter.com/DalianaLiu
00:00:00 Introduction
00:01:28 Get into computer science from non-tech background
00:03:08 How he started his first project
00:04:07 Projects at Airbnb
00:06:09 Speed vs Quality when building data pipelines
00:16:34 How to deal with AdHoc requests
00:21:00 How did he learn machine learning
00:24:04 How he convinced data scientists to teach him ML
00:25:15 Performance review
00:27:11 Don’t let your job title limit your career
00:28:29 Why he started his company
00:31:38 Build your own tool vs use open source solutions
00:33:12 Transitioning from an engineer to a CEO
00:34:50 Earn trust from internal stakeholders
00:36:27 Career advice
00:41:31 How he carved his own path at Airbnb
00:46:00 How did he learn to be a good engineer
00:47:10 Best advice for data scientists or engineers
00:48:41 Most important quality of data scientists or engineers
00:51:51 Design principles
00:58:51 Future of tools
01:01:00 What does he think about his future career
01:05:05 Inspiration of Tommy
