The possibility of moving to different teams and transitioning easily is what makes Amazon a long-term place to work.
Each org feels like a different company altogether. The career progression and mentoring are greatly valued.
Some teams are good, and then some teams are bad, but the overall culture at Amazon is not structured to be constructive and weed out the bad environments.
Value the feedback from team members more to hear the voice of individuals. Connections aren't being taken seriously in some organizations, which leads to toxic culture and behavior enablers.
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.
3-Round Interview Process: 1st and 2nd rounds: Technical interview, solving Python and SQL questions. 3rd round: Loop interview with 5 rounds (Data Engineer, BI Engineer, Manager, and Bar Raiser). The team was based out of Seattle. On-site.
The Amazon interview was straightforward and very technical. It focused mainly on the techniques we approach day-to-day. Behavioral questions were asked using the STAR method, centered around Amazon’s Leadership Principles. Interviewers were profe
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.
3-Round Interview Process: 1st and 2nd rounds: Technical interview, solving Python and SQL questions. 3rd round: Loop interview with 5 rounds (Data Engineer, BI Engineer, Manager, and Bar Raiser). The team was based out of Seattle. On-site.
The Amazon interview was straightforward and very technical. It focused mainly on the techniques we approach day-to-day. Behavioral questions were asked using the STAR method, centered around Amazon’s Leadership Principles. Interviewers were profe