Senior Software Engineer

Straive; Chennai District; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Straive in Chennai is looking for a Senior Software Engineer to build core data processing and application infrastructure using Java and Apache Spark. The role demands deep hands-on expertise in the Java ecosystem, distributed computing, and modern cloud-native patterns.

You will architect and implement mission-critical systems that process massive datasets, requiring mastery of concurrency, JVM internals, and Spark optimizations.

Qualifications

• Expert in Java with strong concurrency and JVM tuning.
• Proven experience designing Spark-based data processing pipelines.
• Strong Spring Framework in production environments.
• Hands-on with Docker/Kubernetes/OpenShift in cloud-native deployments.
• Experience with SQL and NoSQL databases at scale.

Responsibilities

• Architect and build high-throughput, low-latency data pipelines using Spark and the Spring ecosystem.
• Lead performance tuning, GC optimization, and Spark job profiling.
• Design resilient distributed data stores and secure coding practices.
• Mentor engineers and drive adoption of modern architectures across the team.

Skills

Java

Apache Spark

Distributed systems

JVM tuning

Spring Framework

Cloud native OpenShift/Kubernetes

Tools

OpenShift

Maven/Gradle

Jenkins

Git

Spark SQL/DataFrames

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:

• Big Data Ecosystem: Hadoop, Hive, Impala, Spark Tuning & Optimization
• Databases: Relational (e.g., PostgreSQL, Oracle), NoSQL (MongoDB, Graph DB)
• 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 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:

JVM: Expert-level proficiency in Java, including the Collections Framework, Lambdas, and the Java Concurrency API. Demonstrable experience tuning the JVM and 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.