[Remote] Data Software Engineer
Note: The job is a remote job and is open to candidates in USA. EPAM Systems is seeking a Data Software Engineer to create data-focused applications using Big Data tools and cloud technologies. The role involves developing analytical solutions, leveraging AWS services, collaborating with cross-functional teams and clients, and ensuring solution quality through testing, code reviews, and documentation.
Responsibilities
- Engineer and enhance data software applications that support Data Integration Engineers
- Design and deploy advanced analytical solutions using Spark, PySpark, NoSQL, and other Big Data tools
- Leverage AWS services to add cloud features that improve data workflow efficiency
- Partner with product and engineering teams to gather requirements and enable decision support
- Collaborate with architects, technical leads, and other teams to maintain solution consistency
- Assess business goals and technical constraints to recommend the right implementations
- Lead code review activities to encourage best practices and strong code quality
- Execute validation and testing across functional, technical, and performance criteria
- Produce and maintain detailed documentation to support ongoing development
- Work directly with clients to understand needs and provide expert technical direction
Skills
- Bachelor's or Master's degree in Computer Science, Software Engineering, or a related area
- 2+ years of hands-on Data Software Engineering experience with Big Data technologies
- Good command of data engineering principles covering data management, storage, visualization, operations, and security
- Strong grasp of ingestion pipelines along with Data Warehousing and Data Lakes
- Programming experience in Python, Java, Scala, or Kotlin
- Advanced knowledge of SQL and NoSQL data stores
- Proficiency with Spark and PySpark in production data solutions
- Ability to architect and deploy AWS-based solutions using Glue and RedShift
- Familiarity with CI/CD approaches for integration and deployment workflows
- Exposure to Docker, Kubernetes, and Yarn for containerized delivery
- Working experience with Databricks for analytics and data engineering
- English level of minimum B2 (Upper-Intermediate) for effective communication
- Working knowledge of Hadoop, Hive, Flink, and related Big Data tooling
- Understanding of SDLC methodologies with Agile as a key approach
- Experience applying and governing SDLC implementation practices
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
Company Overview
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