Senior Software Engineer - Risk Services Java / Python - CRISIL - #2127583

We are seeking a Senior Software Engineer to join the Risk Services team within Global Markets . This role focuses on designing and building scalable, distributed systems that support risk data processing, analytics and reporting workflows .

The ideal candidate will have strong experience across Java and Python-based backend systems , with a solid understanding of risk data flows, distributed architectures and enterprise-grade platforms .

Key Responsibilities

1. Design, develop and enhance backend services and distributed systems supporting risk data and analytics platforms
2. Build and maintain scalable applications using Java (Spring / Spring Boot) and Python
3. Develop solutions for risk data ingestion, transformation and processing pipelines
4. Contribute to system architecture, design reviews and performance optimization
5. Work with large datasets to support risk calculations, reporting and downstream analytics
6. Collaborate with risk, front-office and data teams to translate requirements into robust technical solutions
7. Participate in code reviews, testing and release processes ensuring high-quality delivery
8. Troubleshoot and resolve issues in production systems , focusing on stability and performance

Must-Have Skills

1. Strong experience in Java (Spring / Spring Boot) and Python development
2. Proven experience building distributed systems and microservices architectures
3. Strong understanding of data structures, algorithms and system design principles
4. Hands-on experience working with large-scale data processing systems
5. Experience with messaging frameworks (e.g., Kafka, MQ)
6. Strong working knowledge of Unix/Linux environments
7. Experience with XML and enterprise data integration patterns
8. Experience with modern development practices , including CI/CD pipelines, Build and deployment processes, Unit and integration testing

Domain Experience (Preferred)

1. Understanding of Global Markets products , including Rates, Credit, Equities, Derivatives
2. Exposure to risk data flows and analytics pipelines within capital markets
3. Familiarity with Risk reporting systems, Trade lifecycle and PnL workflows
4. Experience working in enterprise financial platforms or similar large-scale environments

Good-to-Have

1. Exposure to high-performance or low-latency systems
2. Experience with data streaming and real-time processing frameworks
3. Familiarity with cloud or containerization technologies (Docker, Kubernetes)
4. Prior experience in global banking or financial services environments

Experience

1. Around 9–15 years of experience (flexible for strong candidates)