Senior Data Engineer (PySpark, NoSQL)

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

• 5+ years of experience as a Data Engineer or similar role
• Strong hands-on experience with PySpark in production
• Proven experience in data modeling, partitioning, indexing, and performance tuning in NoSQL systems
• Strong programming skills in Python
• Experience building and operating production-grade pipelines in cloud (Azure)
• Experience with distributed NoSQL databases (e.g., Cosmos DB, Cassandra, DynamoDB, MongoDB)
• Strong understanding of distributed systems and performance optimization
• Experience with CI/CD, monitoring, troubleshooting, and production support
• Strong analytical and communication skills (English B2+)

Nice to have:

• Experience with real-time / streaming data
• Exposure to Data Science workflows
• Knowledge of Big Data ecosystems
• Experience with financial data
• Familiarity with AI-assisted development or LLM tools

• Design and optimize large-scale data pipelines using PySpark
• Build and maintain scalable ETL/ELT workflows in Azure
• Troubleshoot production issues related to performance, latency, and availability
• Work with distributed NoSQL technologies (e.g., Cosmos DB, Cassandra, DynamoDB, MongoDB, or similar)
• Optimize Spark jobs (partitioning, execution plans, resource usage)
• Implement best practices for scalability, security, and reliability
• Collaborate with cross-functional teams on data-driven solutions
• Contribute to automation, CI/CD, and operational improvements