Roles and Responsibilities

- Architect, build, and optimize high-throughput, low-latency distributed data processing pipelines using Apache Spark and Java.
- Perform deep JVM garbage collection tuning and optimize Spark job execution plans for high-volume data workloads.
- Design and deploy resilient, containerized microservices using Docker, Kubernetes, and OpenShift environments.
- Implement robust backend services and batch processing components utilizing Spring Boot, Spring Data, and Spring Batch.
- Model, query, and optimize relational databases (PostgreSQL/Oracle) and NoSQL stores (MongoDB/Graph DB).
- Drive engineering best practices by writing automated test suites using JUnit and Mockito under a TDD/DDD methodology.
- Automate, maintain, and upgrade end-to-end CI/CD build and deployment pipelines using Maven, Gradle, Jenkins, and Git. Provide technical leadership, participate in architecture design reviews, and mentor junior software engineers.





Preferred Candidate Profile

Experience: 7 to 10 years of overall software engineering experience with a strong focus on Core Java and Big Data engineering.

Technical Expertise:

- Expert-level Core Java (8+), Java Concurrency API, Collections, and JVM internals tuning.
- Proven track record with Apache Spark (RDDs, Data Frames, Spark SQL) for large-scale data transformation.
- Production experience with the Spring Ecosystem, specifically Spring Boot, Spring Batch, and Spring Data.
- Hands-on expertise with Docker containerization and orchestration via Kubernetes or OpenShift.
- Solid command of SQL (PostgreSQL, Oracle) along with NoSQL solutions like MongoDB.
- Solid foundation in Data Structures, Algorithms, SOLID design principles, and Test-Driven Development (TDD).

📌 Senior Java Developer (Chennai)
🏢 SG Analytics
📍 Chennai