Former senior hire at Bloomberg - Senior Software Engineer Bloomberg Employee Review

4.0
May 27, 2024
Recommend
CEO approval
Business Outlook

Pros

Bloomberg is pretty chill as far as fintech goes. Best strategy is to put in the hard work for the first two years and learn their home-grown ecosystem. You mileage may vary, but once I've earned my status, I'd get away with ~20 hours of work a week

Cons

Bloomberg is very, very "cliequey" if thats a word. They pride themselves on their FST bootcamp and you'll quickly learn that most of your senior colleagues have grown up within the company with the same people they did the bootcamp with. Additionally, note the power dynamics of people on the US work visa. Many of them need to bite their tongue for years while they wait for a green card. Managers get used to quiet people and kinda of freak out, once a rare disagreable employee tells them "no". tl;dr You'll need to play careful political game if you enter Bbg as a senior tech hire to succeed. Tech stack is home grown and kind of peculiar. But the chill pace of the company makes up for it.

Explore other reviews about Bloomberg

5.0
Jun 22, 2026
Recommend
CEO approval
Business Outlook

Pros

Good management + good people + work life balance

Cons

NA - can be stressful

4.0
Jun 28, 2026
Recommend
CEO approval
Business Outlook

Pros

Opportunities to do lots of work with data and finance to apply knowledge in both programming and Subject-Matter Expertise (SME). Excellent Work-Life Balance (WLB) and extremely welcoming culture. You can reach out to anyone for help or just to talk, and they will get back to you (although management does require more scheduling in advance). Generous compensation (good wage) and benefits, including housing for interns. If you heard the rumors that the Bloomberg Princeton office has a great Bloomberg Pantry (read: company-provided breakfast and lunch), the rumors are true.

Cons

Not the place for those looking for cutting-edge AI. The company is not as fast with AI as the company prioritizes reliability and accuracy above all, and much of AI is not at an acceptable threshold for management to be willing to take that risk with financial data (at least in 2026). You may get a project to automate menial processes, which is really cool, but that tends to involve actually doing the menial processes, which feels unproductive. Princeton office is good but New York is considered preferable. Coworkers are not very reachable outside of work hours. Compensation is low in Data compared to Software Engineers.

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