Senior Java Engineer (Iceberg + QuickSight)

Job description

**Project Description:** We are looking for a Senior Java Engineer to join our Capital Markets technology team and contribute to building a modern analytics platform. This role combines strong backend engineering expertise with hands-on work across the data layer and visualization layer, leveraging technologies such as Apache Iceberg and Amazon QuickSight. You will work on client-server analytics applications, primarily on the backend, while playing a key role in enabling scalable data solutions and delivering business insights. **Responsibilities:** Key Responsibilities Design and develop robust Java-based backend services for analytics applications Build and optimize data pipelines and storage solutions using Apache Iceberg Work with large-scale financial datasets, ensuring performance and scalability Enable reporting and insights through integration with Amazon QuickSight Develop APIs supporting both real-time and batch analytics workflows Collaborate closely with data engineers, analysts, and business stakeholders Contribute to architecture decisions, system design, and best engineering practices **Mandatory Skills Description:** 7–10+ years of experience in Java development (Java 8+) Strong experience with Spring / Spring Boot ecosystem for building enterprise applications Experience designing and building RESTful APIs and microservices architectures Solid understanding of containerization and deployment (Docker; Kubernetes is a plus) Experience with distributed systems, multithreading, and performance optimization Hands-on experience with data lake technologies (Apache Iceberg preferred) Strong proficiency in SQL, data modeling, and large-scale data processing Experience with AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, etc.) and integrating them into daily workflows Familiarity with Agentic SDLC concepts (AI-driven development workflows, automation of coding/testing/review processes) Experience working with capital markets systems (trading, risk, or analytics) Strong understanding of software engineering best practices (CI/CD, testing frameworks, code quality, version control) **Nice-to-Have Skills Description:** Knowledge of AWS ecosystem (S3, Athena, Glue, QuickSight, IAM, etc.) Experience with Kafka, Spark, or other data processing frameworks Familiarity with microservices and cloud-native architecture patterns Knowledge of financial instruments and analytics workflows