Overview

We are looking for a highly skilled and experienced Data Software Engineer to join our team and assist in creating data-centric applications.

You will leverage advanced Big Data tools, cloud technologies, and collaborate with various teams to deliver innovative solutions for complex business challenges.

Responsibilities

  • Build and improve data software applications used by Data Integration Engineers
  • Develop and release advanced analytical solutions using Spark, PySpark, NoSQL, and other Big Data tools
  • Implement cloud-based capabilities on AWS to streamline and optimize data workflows
  • Collaborate with product and engineering teams to gather input and support data-informed decisions
  • Align with architects, technical leads, and partner teams to deliver consistent end-to-end solutions
  • Evaluate business requirements and technical landscapes to propose appropriate technical implementations
  • Perform code reviews to reinforce best practices and maintain high code quality
  • Test and validate solutions against functional, technical, and performance expectations
  • Document deliverables thoroughly to support future maintenance and enhancements
  • Engage with clients to capture requirements and provide expert technical guidance

Requirements

  • Bachelor's or Master's degree in Computer Science, Software Engineering, or a related discipline
  • Relevant experience in Data Software Engineering with 2+ years working with Big Data technologies
  • Solid understanding of data engineering fundamentals such as data management, storage, visualization, operations, and security
  • Deep knowledge of data ingestion pipelines, Data Warehousing, and Data Lakes
  • Hands-on programming skills in Python, Java, Scala, or Kotlin
  • Proven ability with SQL and NoSQL databases
  • Practical expertise in Big Data tooling, especially Spark and PySpark
  • Experience designing and deploying solutions on AWS, including Glue and RedShift
  • Working knowledge of CI/CD pipelines and deployment workflows
  • Familiarity with containerization and tools such as Docker, Kubernetes, and Yarn
  • Experience using Databricks for advanced data analytics and engineering
  • English proficiency at B2 (Upper-Intermediate) level or higher, written and spoken

Nice to have

  • Exposure to additional Big Data tools such as Hadoop, Hive, and Flink
  • Knowledge of SDLC methodologies with an emphasis on Agile practices
  • Ability to implement and manage SDLC processes effectively

[GTS] Benefits (generic, except India)

  • International projects with top brands
  • Work with global teams of highly skilled, diverse peers
  • Healthcare benefits
  • Employee financial programs
  • Paid time off and sick leave
  • Upskilling, reskilling and certification courses
  • Unlimited access to the LinkedIn Learning library and 22,000+ courses
  • Global career opportunities
  • Volunteer and community involvement opportunities
  • EPAM Employee Groups
  • Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn