LinkedIn Data Engineering with Kapil Surlaker

A large social network needs to develop systems for ingesting, storing, and processing large volumes of data. Data engineering at scale requires multiple engineering teams that are responsible for different areas of the infrastructure. Data needs to be structured coherently in order to minimize the data cleaning process. Machine learning models need to be developed,