How is it to lead an all-remote, globally distributed team?
summary
An all‑remote data platform runs on Snowflake and Airflow, executes about 250k queries/day, processes ~2,700 daily models and runs 88 active Airflow flows across ~45 sources with a 25‑source backlog. The org has zero offices, 1,800+ employees and a 2,500‑page public handbook. Hiring yields hundreds to thousands of applicants per role (examples: 173 and 1,967). Work uses quarterly OKRs, a planning drum, weekly 1:1s, onboarding issues, a manager Elevate program and metrics focused on results not hours.
AI-written summary · about
chapters (20)
- 0:00Leading globally distributed teams
- 1:49Office to all-remote work
- 3:58GitLab’s remote mission
- 5:25Data platform team structure
- 7:11Data platform scale
- 8:18Advantages of global teams
- 9:21Quarterly planning priorities
- 10:03Remote communication tools
- 11:28Building trust remotely
- 13:13Performance management
- 15:19Feedback importance
- 16:23Team growth model
- 17:06Measuring team success
- 18:27Q&A: Remote skepticism
- 20:03Q&A: Onboarding new members
- 21:14Q&A: People vs project management
- 22:17Q&A: Meetings and time zones
- 23:51Q&A: Data privacy handling
- 24:41Q&A: Availability and time zones
- 25:48Q&A: In-person meetings
related talks
40mDo the Magic with All-Remote Data Teams...
13mManaging Remote Teams
56mRemote HighLoad
36mRemote work is here to stay: and what's next?
14mHome is where the CEO is
41mElastic: How a Fully Distributed Team of 250 People Works
01h 10mLeading successful remote teams
28mMaking do: Scaling expertise on teams you can't grow