You will contribute to the development of scalable backend services and data infrastructure that power a complex, service-oriented platform used by global clients and professional users. The role combines backend development with data pipeline and infrastructure work in a high-performance environment.

• Designing, developing, and maintaining scalable backend services using Java/Kotlin.
• Building and enhancing RESTful APIs and high-performance systems handling large-scale workloads.
• Developing and maintaining Spark ETL pipelines and data workflows.
• Supporting and evolving data infrastructure, including data lakes, reporting, and analytics tools.
• Implementing new features that improve system performance and user experience.
• Monitoring application metrics, responding to alerts, and ensuring high availability and reliability.
• Optimizing services, databases, and infrastructure for performance, cost-efficiency, and maintainability.
• Participating in architecture discussions and conducting in-depth code reviews.
• Ensuring robust security, streamlined deployments, and continuous technology improvements.
• Working in a modern engineering environment with continuous deployment, full test automation, and service-oriented architecture.

We are looking for a Senior Java Engineer with a strong backend background and a growing interest in data engineering, who enjoys working on scalable, high-load systems and modern data infrastructure in a fast-paced, technology-driven environment.

• 6+ years of hands-on experience in Java development.
• Strong experience in designing and building HTTP/REST APIs.
• Solid knowledge of relational databases and server-side development.
• Practical experience with AWS and Linux-based environments.
• Experience with Spark, ETL pipelines, or big data storage formats (or a strong willingness to learn).
• A good understanding of distributed systems, asynchronous patterns, and messaging technologies.
• Strong knowledge of design patterns and scalable system architecture.
• Openness to modern development practices and AI-assisted engineering tools.
• Good spoken English for stakeholder communication and troubleshooting.
• Nice to have: experience with Python, NoSQL databases, large datasets, and cloud storage such as Amazon S3.
• A mindset aligned with DevOps culture, automation, clean code, and continuous improvement.