Data Engineer applicants have rated the interview process at Amazon with 3.2 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 52% positive. To compare, the company-average is 57.5% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Engineer roles take an average of 27 days to get hired, when considering 187 user submitted interviews for this role. To compare, the hiring process at Amazon overall takes an average of 28 days.
Common stages of the interview process at Amazon as a Data Engineer according to 187 Glassdoor interviews include:
Phone interview: 34%
One on one interview: 19%
Skills test: 15%
Presentation: 10%
Group panel interview: 7%
Personality test: 5%
IQ intelligence test: 4%
Background check: 3%
Other: 2%
Drug test: 1%
Here are the most commonly searched roles for interview reports -
I applied through other source. I interviewed at Amazon (Seattle, WA) in May 2017
Interview
First, the hiring manager contacted me on LinkedIn. After which I was asked for my resume and then HR setup the technical phone screening. Interviewer showed up about 10 mins late and took about 1 hour for the entire process.
Interview questions [1]
Question 1
Usual stuff - tell me about your work experience, current project etc.
Then proceeded to their online SQL coding site. Given sample tables and asked various questions involving Outer Joins & Cross Joins, Sub Queries, Query to fill missing data etc
I applied online. I interviewed at Amazon in Jun 2026
Interview
Applied online. Got an OA. OA was not that difficulty, on the easier side to be honest. Got an email asking for interview availability.
Interview in a week. Will update soon.
Very difficult process it took me a round 1 month to get back what’s the review for the interview so I think overall it’s bad experience and difficult interview process while it has lot of questions I wa able to answer
Standard three-round process consisting of an online assessment followed by a comprehensive interview loop, where candidates were evaluated across technical skills, problem solving ability, and overall fit for the role.