How to Build an On-Call Culture in a Data Engineering Team

Atany company, one of the best ways to gain and retain customers is to deliver excellent services, meaning the service should be healthy and functional whenever the customers access it. To achieve this, the tech industry introduced on-call duty which was often associated with doctors in the past. The definition of on-call varies among companies. But here is the general description: Being on-call means being available and ready to respond to production incidents with appropriate urgency during a certain period of time. On-call is often associated with Software Engineers and Site Reliability Engineers (SRE) to support software such as APIs, websites, mobile apps, IoT services and etc. Data engineers, on the other hand, seem to be not engaged with on-call duty as much as their peers. I will explain the reasons in a second. But this is going to change. As someone who is interested in multidisciplinary, I want to share how we can set up an on-call culture in a data engineering team. Most of the experiences come from my current team, but I would like to hear how you do it in your team and any interesting thoughts down the line. <h2>Why on-call wasn’t a thing for data engineers?</h2> On-call can be stressful. When a production issue kicks in, engineers immediately get paged inside or outside of regular working hours and do their best to do the first steps of incident management. They are aware that anxious customer are eagerly waiting for service to be restored. They understand that a prolonged delay in fixing the issue would result in the loss of customers and revenue for the company. <a href="https://towardsdatascience.com/how-to-build-an-on-call-culture-in-a-data-engineering-team-7856fac0c99">Visit Now</a>