PINTEREST
As Burgess explains , one of the biggest challenges in data engineering is improving Pinterest ’ s developer productivity , which is measured through surveys and the time taken to complete tasks : “ For example , the time it takes to train and deploy a new machine learning model or run an experiment .”
From the survey results , a developer productivity NPS ( Net Promoter Score ) is calculated , from + 100 to -100 . “ When I first started at Pinterest four years ago , our developer productivity NPS was -5 and now it ’ s + 65 .”
Since joining the business four years ago , Burgess has overseen the replacement of many of Pinterest ’ s data engineering systems with the latest in open-source software . “ We ’ ve also built machine learning and experimentation platforms on top of our data platform , increased ML Engineering velocity by 10x and run hundreds of new experiments every week ,” he adds . “ We ’ ve also democratised our data so that everyone in the company can use data to make decisions , build applications and experiment . All of this has significantly improved our agility , developer productivity , and the products for our customers .”
2010
Year founded
$ 2.8bn
Revenue in 2022
4K +
Employees around the globe
460m +
Monthly users pinterest . com 7