Data Engineer applicants have rated the interview process at Virtusa with 2.5 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 100% positive. To compare, the company-average is 69.1% positive. This is according to Glassdoor user ratings.
Common stages of the interview process at Virtusa as a Data Engineer according to 2 Glassdoor interviews include:
IQ intelligence test: 17%
Presentation: 17%
Personality test: 17%
Drug test: 17%
Other: 17%
Phone interview: 17%
Here are the most commonly searched roles for interview reports -
I applied online. I interviewed at Virtusa (Boston, MA) in Dec 2020
Interview
1st HR round - General background questions.
2nd Code Challenge - includes Hadoop, Python, SQL Java.
3rd Technical round - Asked about python, Hive, HDFS, Spark.
what is external table and internal table in Hive.
Why do we dopartition in Hive.
Interview questions [1]
Question 1
what is external table and internal table in Hive.
Why do we dopartition in Hive.
Method Overloading, Method Overidding. SQL Joins.
How to get content which is not included in inner Join.
I applied online. I interviewed at Virtusa (Pune) in May 2026
Interview
I interviewed at virtusa, first round was AI round, then L1 interview they scheduled , asked some scenarios based questions. but they havent reached at me for next level. Interviewer asked me about the SQL and Pyspark
I applied through a recruiter. I interviewed at Virtusa (Málaga) in Nov 2025
Interview
Me preguntaron cosas muy concretas de PowerBi que no me acordaba. No entiendo la importancia que le dieron a las preguntas cuando había cosas más importantes y que le podría dar mejores resultados con otros visualizadores.
Interview questions [1]
Question 1
Me preguntaron sobre PowerBI principalmente, pero en la oferta no parecía relevante.
I applied through a recruiter. I interviewed at Virtusa (Bengaluru)
Interview
it was virtual intervirew 3 rounds, asked on spark architecture , pyspark , sql
prep well on project you did.sql on window functions .
data modelling questions , pyspark optimizaions.