Full Stack Software Engineer — Java / Spring Boot / Kafka / GraphQL

Job Description

We're looking for a versatile full stack engineer to help modernize our API platform. You'll work on evolving existing Java/Spring Boot REST services — refactoring how they source and serve data, integrating GraphQL-based data access, and consuming real-time event streams. This is a hands-on role for someone comfortable picking up any task across API, streaming, and data layers.

Key Responsibilities

• Enhance and refactor existing Java / Spring Boot REST APIs, including re-platforming their data access layers.
• Design and integrate GraphQL services — schema design, queries/mutations, resolvers, federation, and client integration from Spring Boot (Spring for GraphQL, DGS, or similar).
• Build and maintain Kafka streaming components that feed and synchronize downstream data stores and APIs (producers, consumers, Kafka Streams, Avro/Schema Registry).
• Work with Microsoft SQL Server — understand existing schemas, queries, and stored procedures to accurately migrate data access logic without breaking contracts.
• Own features end to end design, implementation, testing, code review, deployment, and production support.
• Maintain backward compatibility of public API contracts during migration; version and document APIs (OpenAPI/GraphQL schema).
• Write automated tests (JUnit, Mockito, Testcontainers) and contribute to CI/CD pipelines.

Required Skills

• Min 8+ years of Java and production Spring Boot REST API development.
• Hands-on GraphQL experience — schema modeling, resolver implementation, and consuming GraphQL from backend services.
• Solid Apache Kafka experience: event-driven design, serialization/schema evolution, consumer groups, offset and error handling.
• Strong MS SQL Server / T-SQL skills and query tuning.
• Experience migrating or refactoring legacy services to new data sources or architectures.
• Git, Maven/Gradle, Docker, Kubernetes, and CI/CD tooling.
• Strong debugging skills across service, stream, and database boundaries.
• Practical experience applying AI/LLM-based developer tools to speed up day-to-day engineering work, with good judgment on where they help and where they don't.