"I know I'll always have mentors that have a real interest in my career, and that they will help me navigate the various products and technologies used at Bloomberg."
I joined Bloomberg last summer as part of my Industrial Placement during university and worked for six months in the Derivatives Pricing Library team, which is responsible for researching and building the high-performance distributed infrastructure that underpins Bloomberg’s cross-asset derivatives pricing solution. After that, I was lucky enough to get an offer, and I started my full-time role in September of last year.
I can’t stress enough how awesome the culture is here at Bloomberg. While ’transparency’ and ‘collaboration’ have become buzzwords nowadays, you can definitely see them in action here. From being able to see everyone's calendars, meetings, and software they've worked on, to being able to add time on their schedules and ask anyone (regardless of their role) any question.
I've been here less than a year, so I'm obviously still learning and discovering a lot. This has been made so much easier by the fact that people are so keen to help and are organised in Guilds that specialize in different technologies (which have saved my day on multiple occasions).
To top it off, and to make my case about how Bloomberg’s culture is here to stay, I recently learned from someone who has worked here for more than 10 years that the company’s culture has always been like this (and the company is now 40 years old)!
Our team is responsible for the entitlement (data permissioning) infrastructure that is critical for on-boarding third-party datasets into the Bloomberg ecosystem. We're aiming to provide internal clients with the tools to describe complex privileging rules for their data, while maintaining a level of transparency that makes it easy to understand why an individual end-user has access to specific data points or not.
One of the things I'm working on is enabling an internal client to offer more financial data to Bloomberg users by modifying our system to handle more complex rules.
Another ongoing project involves another engineering team which has to ensure that a sizable volume of financial data – in the realm of billions of data-points – passes all the required privileging checks and is also carefully metered to ensure correct pricing.
I'd say that everything about the scale of our system doubles as both challenging and interesting.
I find that it’s a great learning environment because anything from adding a new feature to on-boarding new clients involves reasoning about the bigger picture: How slow/fast do these new operations need to be? Which part of the system will handle the most work? How can we adjust our design to balance out that workload?
I see myself having a plethora of options in terms of taking on more responsibility, enabling me to develop both from a technical and people management standpoint. I know I'll always have mentors that have a real interest in my career, and that they will help me navigate the various products and technologies used at Bloomberg.