Anuvrat Parashar

Have been programming for over a decade now with some of the languages mentioned above. I am most comfortable with Python and Javascript today and am in the process of learning Elixir and Rust. I have forgotten a lot of C/C++ in the last 10 years that I haven't used them much. Given access to internet, stackoverflow and documentation, I can understand and debug code in almost every language.

Every web application that intends to do something more than serving static html pages needs a backend. I have worked on scores of web applications, often wearing multiple hats; individual backend contributor, deployment automation as devops, fixing UI bugs as a frontend engineer, planning future features as an architect, taking care of their health as site reliability engineer. I like to take full ownership of the applications under my care, work towards automating all mundane tasks.

Realized I enjoyed writing frontend too after over 5 years of imagining that I disliked HTML/CSS/JS and losing a couple of great opportunities.

I realized I was doing DevOps without knowing about it. My knack for automating all mundane tasks was the primary drive for it. It started with automating the deployment of the application I was actively developing at that time and then propagated to other teams and their projects in the company resulting in an organization wide cultural shift. First it was deployment automation, then bringing the infrastructure up from scratch, which was soon followed by disaster recovery for every component of the application. Needless to say, I like to make the applications under my care as resilient as possible and strive to bring the time it takes to revive them if and when something goes horribly wrong. Also, ensuring that the same error never causes that to happen again.

I was introduced to python in 2010 during a local meetup and life has never been the same.

I have architected, developed, maintained and scaled data pipelines since my first day job. Didn't even know back then that it was called Data Engineering. It was fun to reduce manual effort of the Data Entry team, by building pipelines to automate every mundane task. That was followed by collection of analytics for the data scientists in the team to take take insights out of. I have built so many of them, that I feel like a glorified plumber ;)