About 8 months ago, I left graduate school with a doctorate and hazy aspirations to work in Big Data. I was drawn to the field because it seemed like a perfect marriage of my career interests: research and analysis, programming, and real-world applications. However, as a Biologist with limited programming experience, the field felt far from reach. I had coded some projects in the past using MATLAB and R, but I lacked an understanding of Computer Science fundamentals and best practices, not to mention practical experience.
Naturally, I turned to the Internet for help. I enrolled in MOOCs (Udacity’s Introduction to Computer Science is a good one), read a couple digestible CS books (try Computers, Ltd. and the O’Reilly series), and browsed YouTube (there are some great examples of Turing Machines.) I participated in a Software Carpentry bootcamp where I was introduced to Python, SQL, and Git. I was also fortunate to come across the new Institute for Data Science at Columbia and enrolled in their Certification program. The combination of self-study and coursework helped me establish skills and build confidence, and late last fall I started seeking dev positions.
None of this would have been possible, or as enjoyable, without the amazing team that works here. Nearly every member has taken a nontrivial chunk of time to help me trace code, explain concepts on the whiteboard, or provide feedback. It is easy to comprehend how beneficial that has been. Three of the four most recent Datadog hires have had nontraditional backgrounds for Software Engineering, providing a testament to the company’s willingness to invest in its people.
Whether you already have a tech background or are interested in transitioning into the field, I’d love to field your questions about coming to work at Datadog. Shoot me an email at celene [at] datadoghq [dot] com! You can also visit the Datadog Careers page and take a look at the current openings. We look forward to hearing from you!