Senior Software Engineer - Core Java & Apache Spark

Citi; Chennai District; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Citi in Chennai, India is seeking a Senior Software Engineer focused on Core Java, Spark, and distributed data platforms. You will architect and implement scalable pipelines, optimize JVM performance, and drive cloud-native patterns across teams.

The role requires deep Java expertise, Spark experience, and hands-on leadership to deliver mission-critical systems processing large datasets. Competitive compensation and a strong tech stack await.

Qualifications

• Expert-level Java and JVM tuning with GC optimization.
• Hands-on Spark development for large datasets.
• Very strong Spring Framework experience (Boot/Data/Batch/Security).
• Distributed systems background in cloud-native patterns.
• Relational and NoSQL database design and optimization.
• Containerization and CI/CD tooling experience.

Responsibilities

• Architect and build high-throughput data pipelines using Spark and Spring.
• Dive into JVM internals and optimize performance and resource use.
• Design scalable, distributed architectures with Kubernetes/OpenShift.
• Promote SOLID, DDD, and TDD in development practices.
• Model and optimize data for relational and NoSQL stores.
• Own CI/CD pipelines for Java apps and Spark jobs in containers.
• Lead code reviews, mentor engineers, and drive technology adoption.

Skills

Core Java

JVM tuning

Apache Spark

Spring Framework

Distributed systems

Kubernetes/OpenShift

Docker

SQL

NoSQL (MongoDB)

TDD

Tools

Maven

Gradle

Jenkins

SonarQube

Job description

Senior Software Engineer - Core Java & Apache Spark

We are hiring an elite Senior Software Engineer to build and scale our core data processing and application infrastructure. This role demands deep, hands‑on expertise in the Java ecosystem and distributed computing with Apache Spark. You will be responsible for the architecture, design, and implementation of mission‑critical systems that process massive datasets, requiring a mastery of concurrency, JVM internals, and modern cloud‑native patterns.

Core Tech Stack

• Languages & Runtimes: Java (8+), SQL, JVM
• Frameworks & Libraries: Spring (Boot, Data, Security, Batch, Integration), Apache Spark (RDD, Spark SQL, DataFrames/DataSets)
• Big Data Ecosystem: Hadoop, Hive, Impala, Spark Tuning & Optimization
• Databases: Relational (e.g., PostgreSQL, Oracle), NoSQL (MongoDB, Graph DB)
• Messaging & Middleware: JMS, Solace
• Containerization & Orchestration: Docker, Kubernetes, OpenShift
• Build & CI/CD: Maven, Gradle, Jenkins, Git
• Code Quality & Security: SonarQube, TDD (JUnit/Mockito), Secure Coding Practices

Key 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 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.

Job Family Group

Technology

Job Family

Applications Development

Time Type

Full time

Most Relevant Skills

Please see the requirements listed above.

Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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