Great colleagues, huge corporation - Financial Software Developer Bloomberg Employee Review

4.0
Feb 4, 2016
Recommend
CEO approval
Business Outlook

Pros

Working with extremely intelligent, kind, and dedicated people. Learning opportunities never cease in either financial or technical domains. Salary and benefits are unbelievable. The name is well-respected in the financial world. Very tolerant and patient with new developers. Offices throughout the world can make travel a lot of fun.

Cons

By virtue of being such a large company with thousands of developers, Bloomberg can't always offer interesting projects to everyone, so it takes a long time to make tangible impact on a product. Development is very slow because the developer tools are either nonexistent or impossible to use. There are many incomplete home-brew solutions. WIth that said, there has been a lot of effort to correct these issues and retain talent over the years. Not a lot of interaction between the various divisions of the company.

Explore other reviews about Bloomberg

5.0
Apr 22, 2026
Recommend
CEO approval
Business Outlook

Pros

Great culture, benefits, pay, and work-life balance

Cons

The technical challenges can be a bit stagnant. You learn to deal with people rather than systems

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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