Delivery Lead-Java Full Stack Developer

Job Summary

The Senior Full Stack Java Engineer will design, develop, and maintain next-generation Capital Markets platforms using Event-Driven Architecture (EDA), Java microservices, Apache Kafka, and cloud-native technologies. The role will focus on building highly scalable and resilient applications supporting trade capture, lifecycle processing, workflow management, and real-time event distribution across Front Office, Middle Office, and downstream platforms.

The candidate will contribute to systems supporting FX, Rates, Swaps, OTC Derivatives, and post-trade processing workflows while collaborating with business, operations, risk, and technology stakeholders.

Experience with ISDA Common Domain Model (CDM), Databricks, and enterprise data platforms will be an advantage.

Key Responsibilities

• Design, build, and maintain high-performance Java-based microservices.
• Develop scalable, fault-tolerant, and resilient distributed applications.
• Deliver end-to-end solutions spanning UI, backend services, APIs, and messaging layers.
• Build reusable frameworks, components, and libraries.
• Participate throughout SDLC including design, development, testing, deployment, and production support.
• Develop applications utilizing Apache Kafka for event distribution and real-time messaging.
• Build Kafka producers, consumers, and streaming solutions.
• Implement event sourcing, idempotency, retry handling, dead-letter queues, error recovery, and event versioning.
• Design Kafka topics, partitioning strategies, schema management, and consumer optimization.
• Support event replay, resiliency, and high-availability requirements.
• Develop microservices using Java 11/17+, Spring Boot, Spring Cloud, Spring Kafka, REST APIs, and JPA/Hibernate.
• Design and implement integrations across trading, risk, market data, and operational systems.
• Develop secure, scalable, and performant APIs.
• Optimize reliability and performance within distributed environments.
• Build solutions supporting: FX Spot, FX Forward, FX Swaps, Interest Rate Swaps, Cross Currency Swaps OTC Derivatives
• Support trade lifecycle processing from execution through settlement.
• Collaborate with Front Office, Risk, Product, and Operations teams.
• Develop event-driven data pipelines feeding enterprise analytics platforms.
• Support integrations with Databricks and data lake environments.
• Enable regulatory reporting, risk reporting, reconciliation, trade surveillance, and operational analytics.
• Ensure data quality, governance, and lineage standards.
• Support adoption of ISDA Common Domain Model (CDM).
• Contribute to event and lifecycle modelling.
• Enable standardized trade lifecycle processing and canonical business event structures.
• Promote cross-platform data consistency.

Key Competencies

• Strong hands-on experience in Java (Java 11/17+) development.
• Expertise in Spring Boot, Spring Cloud, Spring Kafka, and JPA/Hibernate.
• Experience designing and developing Microservices-based applications.
• Strong knowledge of Event-Driven Architecture (EDA) principles.
• Hands-on experience with Apache Kafka, Kafka Streams, and Kafka Connect.
• Experience building Kafka producers, consumers, and stream-processing applications.
• Strong expertise in REST API design, development, and integration.
• Experience with distributed systems and scalable application architecture.
• Good understanding of event sourcing, idempotency, dead-letter queues (DLQ), retry mechanisms, and event versioning.
• Proficiency in Oracle, PostgreSQL, SQL Server, MongoDB, and Redis.
• Experience with AWS and/or Azure cloud platforms.
• Hands-on experience with Docker and Kubernetes.
• Experience implementing Infrastructure as Code (Terraform).
• Knowledge of CI/CD pipelines using Jenkins and GitHub Actions.
• Experience with observability and monitoring tools including Grafana, Prometheus, Splunk, ELK Stack, and OpenTelemetry.
• Strong understanding of software engineering best practices, design patterns, and Agile methodologies.
• Experience integrating trading, risk, market data, and operational systems.
• Exposure to Databricks, Apache Spark, Delta Lake, and enterprise data platforms is preferred.

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