It's alright - Recensione dipendente - Software Engineer presso Bloomberg

3,0
31 gen 2021
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

- Work life balance is good, coworkers and management respect your time outside of work - Different areas/aspects of software engineering to take a part in (which means lots of opportunities for internal mobility without needing to move companies) - Center of finance and tech. Lots of opportunities to learn about finance without being in a hedge fund/bank and still do mostly tech work - Although there are still lots of legacy code, there's been a lot of work done to modernize infrastructure and efforts have been showing in the past year. Many teams operate with newer tech

Svantaggi

- Career growth is very unpredictable. You need to be well respected and dignified by management to be considered for promotion. Individual contributors have expectations set by themselves and their team lead, but there aren't ANY measurable metrics for what success means or how much of a raise you're getting.

Esplora altre recensioni su Bloomberg

5,0
8 lug 2026
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

good pay, great team, lots of experience gained

Svantaggi

mundane tasks sometimes, can be competitive

4,0
28 giu 2026
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

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.

Svantaggi

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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