Lead Fullstack Engineer
Join EPAM as a Lead Software Engineer and take full ownership of large-scale, cloud-native data platforms. You will define engineering standards, drive technical strategy, mentor a talented team, and architect resilient systems that fuel sustained business growth across AWS and global markets.
At EPAM, you'll work on cutting-edge technologies, solve complex challenges, and shape the future of digital innovation. With access to continuous learning, mentorship, and global projects, your expertise will drive meaningful change.
Req.#1044865402
Responsibilities
- Design and deliver large-scale cloud-native data platforms on AWS using REST APIs, microservices, and event-driven architectures to build highly scalable and resilient systems
- Work hands-on across a broad technology stack including Java, TypeScript, Angular, Python, and Spark alongside SQL/NoSQL databases to solve complex engineering challenges and maintain platform excellence
- Lead product-wide technical initiatives focused on performance optimization, scalability, reliability, security, governance, and cost efficiency
- Partner with global engineering, product management, architecture, and business stakeholders to align technical solutions with strategic business objectives
- Own the end-to-end software development lifecycle, from requirements gathering and solution design through development, deployment, observability, and documentation
- Mentor and guide junior engineers, fostering a culture of innovation, accountability, collaboration, and continuous technical excellence
Requirements
- 8 to 10 years of software engineering experience with deep expertise in building scalable, UX-driven applications and distributed systems architecture
- Proven hands-on proficiency in Java, Angular, Python, and TypeScript with strong command of object-oriented design patterns and functional programming principles
- Extensive experience with AWS services including S3, Lambda, API Gateway, and EventBridge, combined with Kubernetes containerization and Infrastructure as Code tools such as Terraform and Ansible
- Solid background in data warehousing, data lakes, Delta Lake architectures, and big data technologies including PySpark and Apache Spark for high-performance distributed data processing
- Strong knowledge of event-driven messaging technologies such as Kafka, SNS, and SQS, along with relational and NoSQL databases including PostgreSQL, Aurora, DynamoDB, MongoDB, and Redis
- Demonstrated experience with CI/CD and DevOps practices using Jenkins, GitHub/GitLab, and automated deployment pipelines, paired with robust testing strategies and strong analytical problem-solving skills
