Software Engineer II - Java Full Stack React

Job description

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Software Engineer II - Java Full Stack React Overview: We are looking for a highly skilled and motivated Software Engineer to design, develop, and evolve scalable, reliable, secure, and high-performance applications across the frontend and backend. The ideal candidate will have strong hands-on experience with Java, Spring Boot, REST APIs, gRPC, microservices, React, relational databases, messaging, CI/CD, and cloud-native technologies. The role requires a strong balance of full-stack development, system design, problem solving, technical ownership, AI adoption, and collaboration. The engineer will work closely with product managers, architects, DevOps engineers, and other engineering teams to deliver high-quality solutions from conception through production. Technical Skills & Qualifications : - Overall 3-5 of career experience as a Developer in Full Stack Development - Backend - Strong hands-on experience with Java 17/21+. - Strong experience with Spring Framework / Spring Boot. - Strong understanding of RESTful API design and microservices architecture. - Hands-on experience with gRPC and Protocol Buffers (protobuf). - Good understanding of gRPC concepts including service contracts, streaming, deadlines/timeouts, status codes, error handling, interceptors, and backward-compatible API evolution. - Strong understanding of object-oriented design, SOLID principles, design patterns, and clean code practices. - Experience with JPA/Hibernate and Spring Data. - Strong experience with relational databases such as Oracle, PostgreSQL . - Good understanding of SQL, database design, indexing, transactions, and query optimization. - Experience with Apache Kafka or equivalent messaging/event-streaming technologies. - Good understanding of multithreading, concurrency, caching, transactions, and performance optimization. Frontend - Strong hands-on experience with React. - Strong knowledge of JavaScript and/or TypeScript. - Experience building responsive, reusable, component-based UI applications . - Good understanding of React hooks, state management, component lifecycle, routing, and asynchronous API integration. - Experience with frontend state-management solutions such as Redux, Context API, or equivalent. - Strong understanding of HTML5, CSS3, responsive design, and browser fundamentals. - Experience integrating frontend applications with REST and/or gRPC-backed services. - Understanding of frontend performance optimization, accessibility, security, and browser compatibility. - Testing & TDD - Strong practical experience with Test-Driven Development (TDD) and test-first development practices. - Strong understanding of the Red-Green-Refactor development cycle. - Experience writing effective unit, integration, API, contract, and end-to-end tests. - Backend testing experience with JUnit 5, Mockito, Spring Boot Test, or equivalent frameworks. - Frontend testing experience with Jest, React Testing Library, or equivalent frameworks. - Experience with Playwright, or similar end-to-end testing frameworks. - Ability to design testable code and identify appropriate testing boundaries across unit, integration, and E2E layers. - Ability to incorporate automated tests into CI/CD pipelines and enforce quality gates. - AI-Assisted Engineering - Practical experience using AI coding assistants and developer productivity tools such as GitHub Copilot, ChatGPT, or equivalent tools. - Ability to effectively use AI for code generation, refactoring, test generation, debugging, documentation, code review, and technical analysis. - Ability to write effective prompts and provide appropriate context to AI tools to achieve high-quality engineering outcomes. - Ability to validate, review, and improve AI-generated code rather than relying on AI output without engineering judgment. - Understanding of responsible AI adoption, including data privacy, security, intellectual property, confidentiality, and organizational AI usage policies. - Willingness to continuously evaluate and adopt emerging AI-assisted engineering practices that improve developer productivity and software quality. Key Responsibilities: - - Design, develop, test, deploy, and maintain full-stack applications using Java/Spring Boot and React. - Develop scalable and maintainable backend services using Java and Spring Boot. - Design and implement REST APIs, gRPC services, microservices, and event-driven components. - Develop responsive, reusable, and maintainable user interfaces using React, JavaScript/TypeScript, HTML, and CSS. - Design appropriate communication patterns using REST, gRPC, and asynchronous messaging based on business and technical requirements. - Own software development initiatives end-to-end, from requirements and technical design through implementation, testing, deployment, and production support. - Participate in architecture and technical design discussions with a focus on scalability, performance, availability, security, and maintainability. - Design efficient relational database models and develop optimized SQL queries. - Follow Test-Driven Development (TDD) and a test-first approach when developing new features and fixing defects. - Build and maintain automated unit, integration, API, contract, and end-to-end tests across frontend and backend components. - Leverage AI-assisted development tools such as GitHub Copilot and other approved AI coding/productivity tools to improve development speed, code quality, testing, documentation, troubleshooting, and developer productivity. - Identify and drive opportunities to use AI for engineering automation, including code generation, test generation, code analysis, documentation, refactoring, debugging, and developer workflows. - Evaluate AI-generated code and recommendations critically, ensuring correctness, security, maintainability, performance, and compliance before adoption. - Promote responsible adoption of AI tools while following organizational security, privacy, intellectual property, and engineering standards. - Improve engineering productivity through automation, CI/CD, quality gates, AI-enabled workflows, and developer tooling. - Troubleshoot production issues, perform root-cause analysis, and implement sustainable corrective actions. - Conduct code reviews and contribute to coding standards, design guidelines, and engineering best practices. - Mentor junior and mid-level engineers and contribute to technical knowledge sharing. - Collaborate effectively with cross-functional and distributed teams. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.