Software Engineer II

Mastercard is seeking a Software Engineer II for its Business Experimentation and Optimization (BE&O) teams in Dublin. The role involves building scalable, cloud-native full-stack applications for data-driven decision-making, working with Java, TypeScript, React, and Databricks.

• Design, build, and maintain scalable full-stack applications across frontend, backend, APIs, and data-processing layers using modern technologies such as Java/Spring Boot, TypeScript, and React.
• Develop and optimize data-intensive applications leveraging Databricks, Spark, and related platforms to efficiently process, transform, and serve data.
• Contribute to architecture and system design, collaborating with cross-functional teams to deliver scalable, high-quality solutions aligned with engineering best practices.
• Write clean, maintainable, and efficient code, applying strong practices in testing, code reviews, and continuous improvement.
• Identify and resolve performance bottlenecks across services, APIs, data-processing workloads, and user experience.
• Build features that support data-driven decision-making for global customers through analytics and experimentation.
• Collaborate with Product, Data Engineers, QA, and other teams to translate business needs into scalable technical solutions.
• Mentor and support team members while contributing to a collaborative, growth-oriented engineering culture.
• Continuously learn and improve, staying current with technologies and driving enhancements in quality, scalability, and developer productivity.

• 3+ years of experience as a full-stack Software Engineer, with exposure to building applications using modern technologies such as Java/Spring Boot, TypeScript, and React.
• Experience or familiarity with Databricks, Spark, or PySpark is highly desired, particularly for working with data pipelines or analytics-driven applications.
• Foundational understanding of software engineering principles, including object-oriented programming, API design, and scalable system design, is preferred.
• Interest in working with data-intensive applications, including improving performance, scalability, and reliability across services and data-processing layers.
• Strong collaboration and communication skills, with the ability to work effectively with cross-functional teams.
• Curiosity, self-motivation, and a strong willingness to learn, with a growth mindset and interest in solving analytical, data-driven problems in an agile, fast-paced environment.