Join Mastercard as a Lead Software Engineer and spearhead technical innovation for the Transaction Lookup Services (TLS) platform. This pivotal role involves architecting, developing, and supporting robust APIs and data services essential for secure, simple, and smart transaction processing. You will collaborate closely with product, engineering, and operations teams to deliver enterprise-grade solutions for a variety of payment functions, including disputes, chargebacks, refunds, and historical data retrieval. As a leader, you'll set the technical vision, mentor fellow engineers, and champion operational excellence.

Architect and build high-performance microservices and APIs using Java, Spring Boot, REST, and gRPC for critical transaction lookup functions. Design and implement scalable, low-latency data solutions utilizing Oracle, SQL, PL/SQL, Hadoop, Hive, Impala, and Spark. Define robust API contracts, integration patterns, and service standards, ensuring stringent security through TLS/mTLS, OAuth, and JWT. Lead performance optimization efforts across applications and databases, focusing on query tuning, indexing, caching, and capacity planning. Drive modernization with Kubernetes, Docker, cloud-native architectures, and CI/CD pipelines. Collaborate with cross-functional teams to translate business needs into scalable technical roadmaps. Establish best practices through code reviews, automated testing, and architectural governance. Ensure production readiness with advanced observability tools like Splunk, Dynatrace, Prometheus, and Grafana, implementing proactive alerting and dashboards. Lead incident resolution, root cause analysis, and drive reliability improvements to meet stringent SLAs. Mentor and guide software and senior engineers across multiple initiatives. Evaluate and recommend emerging technologies to enhance platform capabilities.

A Bachelor's degree in Computer Science, Engineering, or a related field is required. Candidates should possess 8+ years of experience in designing and developing enterprise applications with Java, Spring Boot, microservices, REST APIs, and distributed systems. Significant expertise in Oracle databases, SQL optimization, data modeling, and performance tuning in high-volume transactional environments is essential. Experience with big data technologies such as Hadoop, Hive, Impala, Spark, or similar platforms is necessary. Proven hands-on experience deploying and operating applications on Kubernetes and containerized environments is a must. A strong understanding of API design, service integration, security frameworks, and authentication mechanisms is expected. Experience implementing CI/CD pipelines with tools like Git, Jenkins, SonarQube, and Artifactory, along with automated testing frameworks, is required. Demonstrated ability to lead technical design sessions, influence architectural decisions, and drive engineering excellence is crucial. Excellent communication and stakeholder management skills are vital for effective collaboration across engineering and business organizations.