Good salary, incredible scale, very hard to grow, and limited technically
Good salary, incredible scale, very hard to grow, and limited technically
Compensation is in the highest range you can get in Berlin.
The scale of projects is sometimes insane, impacting at minimum millions of customers.
A lot of things happen without too much red tape.
There is too much politics. Projects are often just flashy and oriented to get some manager promoted. The amount of work is not crazy, but it requires a lot of overlap with US time zones. The stress is very high.
Try to align the projects and career growth more with the interests of the people of the company, not only with your own promotion and visibility.
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Amazon Interview Experiences
Data Engineer
It was good, but after the ninth round, they rejected. They should have given one more chance to people who reached the ninth round, as they have some ability as well. So, they should also be considered.
Data Engineer
Good interview with some pro-level questions into data and Python. Checked the decision-making skills and mathematical skills of the candidate, communication skills also analyzed, and thereafter few logical questions.
Data Engineer
Python - DSA questions Data Modeling - Asked to design a data model for a transactional database schema. SQL - Simple to medium questions that can be solved easily. Behavioral - Covered questions like those at other companies.
Data Engineer
London, EnglandOctober 31, 2025It was good, but after the ninth round, they rejected. They should have given one more chance to people who reached the ninth round, as they have some ability as well. So, they should also be considered.
Data Engineer
Hyderābād, Telangana, IndiaSeptember 16, 2025Good interview with some pro-level questions into data and Python. Checked the decision-making skills and mathematical skills of the candidate, communication skills also analyzed, and thereafter few logical questions.
Data Engineer
Seattle, Washington, United StatesAugust 17, 2025Python - DSA questions Data Modeling - Asked to design a data model for a transactional database schema. SQL - Simple to medium questions that can be solved easily. Behavioral - Covered questions like those at other companies.
