Ep2. Data Engineering at Uber and Lyft
这一期节目我们和嘉宾泉来聊一聊Data Engineering,在Uber和Lyft的应用和工作体验,对于行业发展的反思与展望,以及对于入行Data Engineering的建议。只要你对Large Scale Data Engineering感兴趣,本期节目都会对你有帮助 :)
这一期节目我们和嘉宾泉来聊一聊Data Engineering,在Uber和Lyft的应用和工作体验,对于行业发展的反思与展望,以及对于入行Data Engineering的建议。只要你对Large Scale Data Engineering感兴趣,本期节目都会对你有帮助 :)
Timestamps:
Timestamps:
- 00:00:00 Intro
- 00:00:40 Data Infrastructure vs Data Engineer
- 00:02:45 Data Engineering 领域介绍
- 00:09:00 Pipeline权限设置
- 00:11:00 Pipeline在Uber的使用场景
- 00:11:45 如何追踪Data Owner
- 00:11:52 如何保护用户数据隐私
- 00:17:16 Data Infra转到Data Engineer的日常工作
- 00:21:44 Data Quality Tier
- 00:32:52 Uber vs Lyft 数据量级和迭代的区别
- 00:35:46 COVID影响
- 00:38:40 对颠覆性产业和商业模式的反思
- 00:40:27 规模效应和数据
- 00:41:26 ML Infra vs Data Infra
- 00:44:47 对新入行Data Engineering的建议
- 00:47:28 联系方式
Links:
- Airflow: https://airflow.apache.org/
- Piper: https://eng.uber.com/no-code-workflow-orchestrator/
- uWorc: https://eng.uber.com/no-code-workflow-orchestrator/
- Amundsen: https://eng.lyft.com/open-sourcing-amundsen-a-data-discovery-and-metadata-platform-2282bb436234
- PII: https://en.wikipedia.org/wiki/Personal_data
- GDPR: https://en.wikipedia.org/wiki/General_Data_Protection_Regulation
- ETL: https://en.wikipedia.org/wiki/Extract,_transform,_load
- 联系泉来:mail@quanlai.li
联系方式:
- 官网: eng.cafe/
- 微信公众号: Eng Cafe
- Twitter: @engcafefm
- Youtube: Eng Cafe
- Email: hi@eng.cafe
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