Responsibilities: Design, develop, and maintain robust, scalable, and maintainable services that meet business requirements and align with company standards Take end-to-end ownership of multiple domains, supporting them throughout their lifecycle (design, development, deployment, monitoring, maintenance) Investigate, resolve, and prevent production incidents to ensure minimal impact on users Collaborate with product managers, architects, and other developers to translate requirements into technical designs and deliver new features Drive improvements in development processes, code quality, testing practices, and system reliability Write clean, well-documented code and ensure proper test coverage (unit, integration, and functional) Actively contribute to the evolution of our microservice architecture while supporting existing systems
Requirements: 5+ years of professional experience in software development with Java Strong knowledge of Java Core (collections, multithreading, streams API) and Java 8+ features (lambdas, optionals, functional interfaces, records, etc.) Solid experience with the Spring stack: Spring Boot, Spring Cloud, Spring Data (JPA, JDBC) Proficiency in object-oriented design, design patterns, and software engineering best practices Hands-on experience with messaging systems (Apache Kafka) Strong SQL knowledge, with experience in relational databases (e.g., SingleStore, Vertica) Experience writing and maintaining tests using JUnit, Mockito, Testcontainers, WireMock, Spring Test Familiarity with CI/CD tools such as TeamCity or Jenkins Strong troubleshooting and debugging skills, including working with monitoring and logging tools (Grafana, Kibana) Willingness to participate in an on-call duty rotation to support production systems, ensuring timely response and resolution of critical incidents Excellent communication and collaboration skills, with the ability to work across teams
Nice to have: Experience with NoSQL databases (e.g., Redis, Aerospike) Hands-on experience with Apache Spark, Apache Airflow, or data processing pipelines Knowledge of Docker and Kubernetes for containerized deployments Familiarity with data lake technologies (Iceberg/Hive) Basic Python scripting for automation and data handling Knowledge of microservice design principles and distributed systems
