Description
Mastercard's Business Experimentation and Optimization (BE&O) teams are seeking a Lead Software Engineer to drive the architecture, design, and development of their next-generation experimentation platform.
As a Lead Software Engineer, you will lead through technical influence, architectural judgment, and execution excellence to help modernize the platform and deliver scalable, secure, cloud-native capabilities for global business users.
Key responsibilities:
- Lead the technical design and delivery of complex, data-intensive software solutions that enable advanced analytics, experimentation, and data-driven decisioning for Mastercard clients.
- Define and drive technical strategy for modernization initiatives, including evolution of legacy systems toward scalable, cloud-native, API-driven, and service-oriented architectures.
- Lead system design across multiple levels of detail, including platform architecture, high-level design, detailed technical design, integration patterns, non-functional requirements, and implementation approach.
- Serve as a hands-on technical contributor, designing, coding, testing, debugging, and delivering production-quality software across the full engineering lifecycle.
- Build and evolve scalable services, APIs, data pipelines, and analytical capabilities using modern engineering practices, cloud platforms, and data technologies such as AWS, Azure, Databricks, Spark/PySpark, and related frameworks.
- Partner closely with product managers, engineering teams, architects, data scientists, QA, security, and operations teams to translate business and functional requirements into robust technical solutions.
- Coordinate and lead technical execution across globally distributed engineering teams, ensuring alignment across regions, time zones, dependencies, design decisions, and delivery milestones.
- Drive architecture and design reviews, code reviews, technical decision-making, and engineering tradeoff discussions to ensure solutions are secure, resilient, observable, performant, maintainable, and aligned with enterprise standards.
- Identify opportunities to improve platform scalability, reliability, developer productivity, operational readiness, and speed of delivery through modernization, automation, reusable patterns, and engineering best practices.
- Provide technical mentorship to junior and mid-level engineers through design guidance, code review, pairing, knowledge sharing, and modeling strong engineering judgment.
Ideal candidate qualifications:
- 8+ years of software engineering experience delivering scalable, high-performance, and reliable software in an agile environment.
- Strong hands-on experience designing and building distributed systems, microservices, RESTful APIs, and cloud-native applications.
- Strong experience with data-intensive applications and analytics platforms; experience with Databricks, Spark, or PySpark is highly desirable.
- Proven expertise leading system architecture, high-level design, detailed design, and end-to-end technical delivery of complex software solutions.
- Experience driving technology modernization initiatives, including cloud adoption, platform transformation, and modernization of legacy applications.
- Hands-on experience with AWS and/or Azure, CI/CD, containerization, Kubernetes, observability, and modern software delivery practices.