Description

Responsibilities:  Architect & Build: Design and construct high-throughput, low-latency data processing pipelines using Apache Spark and the Spring ecosystem. Performance Engineering: Dive deep into JVM internals, garbage collection tuning, and Spark job optimization to maximize performance and resource efficiency. Distributed Systems Design: Implement scalable, resilient, and transactional architectures leveraging container orchestration (Kubernetes/OpenShift) and distributed data stores. Code & Design Excellence: Champion and enforce best practices in software engineering, including SOLID principles, advanced design patterns, Domain-Driven Design (DDD), and Test-Driven Development (TDD). Database Mastery: Engineer and optimize data models for both relational and NoSQL databases, ensuring data integrity, performance, and scalability. CI/CD Automation: Own and enhance CI/CD pipelines for automated build, test, and deployment of Java applications and Spark jobs in a containerized environment. Technical Leadership: Lead design and code reviews, mentor junior engineers, and drive • View Job Posting Details 04:37 pm 14/07/2026 Page 2 of 3 the adoption of new technologies and architectural patterns across the team.

Required Technical Qualifications: Core Java & JVM: Expert-level proficiency in Java, including the Collections Framework, Lambdas, and the Java Concurrency API. Demonstrable experience tuning the JVM and troubleshooting memory/GC issues. Apache Spark: Proven, hands-on experience developing, deploying, and tuning complex Spark applications for large-scale data transformation and analysis. Spring Ecosystem: Extensive, practical experience with the Spring Framework, particularly Spring Boot, Spring Data, and Spring Batch in a production environment.

Data Structures & Algorithms: Deep understanding of fundamental data structures and algorithms, with a focus on their application in distributed computing and performance critical systems. Containerization & Cloud-Native: Hands-on experience with Docker for building images and Kubernetes/OpenShift for deploying and managing distributed applications. Database Engineering: Strong command of SQL and relational database design, including transaction management and indexing. Experience with at least one production NoSQL database (MongoDB, Graph DB, etc.). Architectural Design: Practical application of OOP, SOLID, and DDD principles to build maintainable and scalable systems. You write tests first (TDD) and believe in robust, automated testing

Key Skills

Education

Bachelor's degree