Data Engineer Intern applicants have rated the interview process at Amazon with 3.1 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 82% positive. To compare, the company-average is 57.5% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Engineer Intern roles take an average of 31 days to get hired, when considering 39 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 Intern according to 39 Glassdoor interviews include:
One on one interview: 31%
Skills test: 31%
Phone interview: 17%
Personality test: 8%
Other: 6%
Background check: 4%
Group panel interview: 2%
Presentation: 2%
Here are the most commonly searched roles for interview reports -
I applied online. The process took 1 day. I interviewed at Amazon (Seattle, WA) in Oct 2024
Interview
2 back-to-back rounds focusing on Data Engineering fundamentals about Star Schema, Snowflake schema, Data warehouses, Datalakes, Dimensional modelling, OTLP vs OLAP, behavioral aspects, and very light coding (SQL was simple join and take count based on product, Python - Sort an array without using Sort function)
Interview questions [1]
Question 1
Data Engineering Fundamentals
Leadership Principles
First round was OA with SQL questions, mcqs and 1 DSA then 2 Technical interviews SQL questions like joins, group by, NULL values, SQL theory, easy to medium leetcode, questions on resume
Interview questions [1]
Question 1
Asked me to differentiate between all 3 types of joins
I applied through a recruiter. I interviewed at Amazon (Tel Aviv)
Interview
After submitting my resume, I received a home assignment with one week to complete it. Later, I attended two interviews that included personal and professional questions about my experience, previous projects, problem-solving skills, and relevant technical knowledge.
The process started with an online assessment (OA) that included SQL and data-related questions. The technical interview focused on core data engineering concepts such as normalization, joins, and a self-join problem, along with some discussion on data modeling and query optimization.