Data Software Engineer

We are looking for a highly skilled and experienced Data Software Engineer to join our team to advance the development of data-centric applications.

This role involves working with cutting-edge Big Data tools, cloud technologies, and collaborating across teams to deliver innovative solutions for complex business challenges.

Responsibilities

• Develop and refine data software applications used by Data Integration Engineers
• Build and deploy sophisticated analytical solutions with Spark, PySpark, NoSQL, and other Big Data tools
• Integrate AWS cloud services to improve and automate data workflows
• Support product and engineering teams by collecting insights and enabling better decisions
• Coordinate across architects, technical leads, and other teams to ensure cohesive implementations
• Determine business needs and technical context to deliver appropriate technical solutions
• Conduct code reviews to maintain coding standards and promote best practices
• Validate and test deliverables against functional, technical, and performance requirements
• Maintain thorough project documentation for future reference and iteration
• Interact with clients to clarify needs and provide expert technical advice

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a similar field
• 2+ years of experience in Data Software Engineering focused on Big Data technologies
• Comprehensive understanding of data engineering areas such as data management, storage, visualization, operations, and security
• Strong expertise in data ingestion pipelines, Data Warehousing, and Data Lakes
• Proficiency across Python, Java, Scala, or Kotlin for building data-centric software
• Extensive knowledge of SQL as well as NoSQL databases
• Proven hands-on experience with Spark and PySpark
• Ability to implement and deploy data solutions on AWS, including Glue and RedShift
• Familiarity with CI/CD pipelines and integration/deployment workflows
• Experience with containerization using Docker, Kubernetes, and Yarn
• Practical knowledge of Databricks for advanced analytics and engineering workloads
• English proficiency at B2 (Upper-Intermediate) level or above in speaking and writing

Nice to have

• Familiarity with Hadoop, Hive, Flink, and other Big Data tools
• Knowledge of SDLC methodologies, with Agile experience
• Capability to implement and manage SDLC processes effectively

Benefits

• 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