There are great tools and technologies. There are no boundations over learning and developing new ideas.
Old Amazon values are gone now. They already hired toxic people who reached at upper levels.
Toxicity seems to be increasing within Amazon, particularly in the Data Engineering team in Gurgaon. There appears to be significant favouritism at the L5 and L6 levels, creating an environment where fair evaluation and equal opportunities are questionable.
New hires often seem to be brought in to support or protect existing employees, rather than being evaluated objectively on their own merits. They are then compared against experienced team members based on internal business knowledge that takes time to acquire. This creates an unfair situation in which new employees are judged negatively for not already knowing systems, processes, and business context that they have not yet had sufficient time to learn.
Instead of fostering collaboration, providing proper onboarding, and evaluating people based on their actual skills and performance, this approach can undermine employee confidence, damage team morale, and create a toxic work environment.
Save Amazon culture! Remove favouritism.
I was interviewed for a Sr. Data Engineer position in Toronto with Amazon Advertising Canada Inc. I had multiple interviews, including an initial tech screen followed by an intensive two-day final round consisting of six interviews. This was one of
It all started with a screening round followed by four onsite rounds. In the screening round, most of the questions were about Python, PySpark, SQL, and Data Warehouses. We had to code the solution for a given problem. 1st round: Python, SQL, PySpa
The interview was poorly structured. It was a telephone interview via AWS Chime, and then I was told to turn my camera on and go through a technical test with only two minutes before introductions. The interviewer backtracked to introductions and ru
I was interviewed for a Sr. Data Engineer position in Toronto with Amazon Advertising Canada Inc. I had multiple interviews, including an initial tech screen followed by an intensive two-day final round consisting of six interviews. This was one of
It all started with a screening round followed by four onsite rounds. In the screening round, most of the questions were about Python, PySpark, SQL, and Data Warehouses. We had to code the solution for a given problem. 1st round: Python, SQL, PySpa
The interview was poorly structured. It was a telephone interview via AWS Chime, and then I was told to turn my camera on and go through a technical test with only two minutes before introductions. The interviewer backtracked to introductions and ru