Glassdoor users rated their interview experience at EPAM Systems as 100% positive with a difficulty rating score of 2.5 out of 5 (where 5 is the highest level of difficulty). Candidates interviewing for Project Manager and UIUX Designer rated their interviews as the hardest, whereas interviews for Project Manager and UIUX Designer roles were rated as the easiest.
The hiring process at EPAM Systems takes an average of 14 days when considering 2 user submitted interviews across all job titles. Candidates applying for Project Manager had the quickest hiring process (on average 14 days), whereas Project Manager roles had the slowest hiring process (on average 14 days).
First round was pen and paper round followed by GD. Main steps include Technical Interview, HR Interview and Managerial round. They check for the confidence and adaptability from candidate. Prepare well and talk confidently
Interview questions [1]
Question 1
Basic Java OOPS concepts and one easy level DSA problem
I applied through a recruiter. I interviewed at EPAM Systems (Buenos Aires) in Jan 2026
Interview
Primera entrevista con RRHH estuvo bien. Experiencia, años trabajados con tecnologias.
Segunda entrevista tecnica. Preguntas muy raras para el puesto, pense que se iban a enfocar en experiencia y no en conocimientos tecnicos. Que en base a la experiencia iban a surgir preguntas sobre las tecnologias usadas. No me preguntaron absolutamente nada pero di una presentacion bastante larga sobre mi.
Interview questions [1]
Question 1
Diferencia entre default y protected.
Nuevas funcionalidades de Java 8
Transient y Volatile
Hashset vs ArrayList
Hoocks de React
Springboot annotations like @Transactional
Ejercicio de sacar el promedio de notas de una lista de estudiantes. Filtrar cada estudiante que tenga nota menor al promedio.
I applied through a recruiter. I interviewed at EPAM Systems (Riyad) in Nov 2024
Interview
I went through a series of technical and non-technical interviews that assessed programming problem solving, SQL querying skills, and Apache Spark knowledge, along with communication ability, logical reasoning, system understanding, and practical experience handling real-world data engineering challenges in a professional environment.