Data Software Engineer - AWS - Java

at  Epam Systems

We are looking for a dynamic Data Engineer who has a blend of traditional Java engineering skills and experience within the Big Data space. This role requires strong knowledge in API development, AWS, and a passion for working with big data technologies like Hive, Hadoop, and Spark. If you enjoy working on an industry-leading Data Platform and contributing to open-source communities, this opportunity is for you!
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.

REQUIREMENTS

• 7+ years of core and server-side Java programming (Spring, concurrency, streams, lambdas)
• Strong knowledge of the Hadoop ecosystem (Spark, Hadoop, Hive)
• Extensive experience with cloud computing platforms (AWS, EMR, S3, Kubernetes, Docker)
• Proficiency with infrastructure-as-code tools (Terraform, Helm)
• Experience with microservice architecture, design, and best practices for scalability
• Familiarity with Agile methodologies (Scrum, code reviews, pair programming)
• Experience with Kafka, including Spark Streaming or Flink
• Strong skills in performance and scalability tuning, algorithms, and computational complexity
• Proficiency in Linux/Python (bash scripting, grep, sed, awk)
• Passionate about open-source contributions

• Write clear, efficient, and well-tested code
• Collaborate with other experienced software engineers to drive improvements to our technology
• Design and develop new services and software solutions
• Build and track metrics to ensure high-quality results
• Work independently with little to no guidance, and support and coach junior team members
• Build rapport with other engineering teams to ensure seamless integration
• Develop scalable and highly performant distributed systems, focusing on availability, monitoring, and resiliency
• Help shape the future of Data Lakes and take architectural ownership for various critical components and systems
• Evolve development standards and design patterns
• Deploy and maintain applications in production environments
• Communicate and document solutions and design decisions effectively