Senior Software Engineer

Novel Financial Solutions; Chennai; Hybrid; INR 1,500,000 - 2,500,000; Part time

Job summary

Novel Financial Solutions in Chennai is seeking a Senior Software Engineer with deep expertise in Core Java, Apache Spark, and the Spring ecosystem. You will architect high-throughput data pipelines, tune JVM performance, and drive scalable distributed systems using Kubernetes/OpenShift.

Responsibilities include leading design reviews, mentoring juniors, and advancing CI/CD for Java applications and Spark jobs in a containerized environment. 6-month contract with hybrid work arrangement.

Qualifications

• Expert-level Java in production environments with strong concurrency control.
• Hands-on Spark development, tuning, and data-processing pipelines.
• Experience with Spring Boot/Data/Batch in cloud-native setups.

Responsibilities

• Architect and build high-throughput, low-latency data pipelines with Spark and Spring.
• Perform JVM tuning, GC analysis, and Spark job optimization for performance.
• Design scalable, fault-tolerant distributed architectures using Kubernetes/OpenShift.
• Uphold SOLID, DDD, and TDD principles across code and tests.
• Model and optimize relational and NoSQL data stores for performance.
• Lead code reviews, mentor engineers, and contribute to CI/CD improvements.

Skills

Core Java

JVM Tuning

Apache Spark

Spring Framework

Distributed Systems

Docker

Kubernetes

SQL

NoSQL

TDD

Tools

Maven/Gradle

Jenkins

Git

OpenShift

Hive/Impala

Spark SQL

Job description

Hi ,

Greetings from Novel Financial Solutions Pvt Ltd.

Novel is one of the Leading companies and we are a 25+ Years old Service Organization with presence in USA, India, Singapore and Hong Kong.

• Role Senior Software Engineer - Core Java & Apache Spark (C13)
• Location- Chennai
• Duration- 06 Months Contract
• No of days of working: 5 Days (Hybrid)

Job Description:

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
• X`x` 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 Frameworks & Libraries: Spring (Boot, Data, Security, Batch, Integration), Apache Spark (RDD, Spark SQL, DataFrames/DataSets)

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

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