Tommy Dang is the Co-founder and CEO of Mage, a data ingestion and transformation pipeline for data engineers (https://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, and 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 www.dalianaliu.com/ for more on data science and career.

Tommy’s LinkedIn: https://www.linkedin.com/in/dangtommy/

Daliana's LinkedIn: https://www.linkedin.com/in/dalianaliu/

Daliana's Twitter: https://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

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