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Luxoft

Senior Java Full-Stack Developer

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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

SKILLS

Must have

  • 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

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