Lead Software Engineer, Cloud Analytics Platform
Mastercard
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Job summary
Mastercard is seeking a hands-on Lead Software Engineer to drive architecture, design, and development of an advanced experimentation platform. You will mentor engineers, guide cross-functional teams, and champion scalable, cloud-native solutions leveraging AWS/Azure and Databricks.
You will collaborate across programs to align goals, define cross-cutting initiatives, and deliver enterprise-grade analytics capabilities.
Qualifications
- 8+ years of extensive software engineering experience in an agile environment.
- Experience building microservices and RESTful APIs, with relational DBs and distributed data stores.
- Cloud experience with AWS and/or Azure; containerization (Docker) and orchestration (Kubernetes).
- Strong data analytics tool experience, Databricks and Spark (or PySpark).
- Ability to translate requirements into scalable technical designs and non-functional requirements.
- Experience incorporating GenAI into software products and lifecycle.
- Proven technical leadership, mentoring engineers and leading cross-functional projects.
- Experience modernizing legacy monoliths to microservice architectures.
Responsibilities
- Build cloud-native services and modern frameworks for large organizations.
- Lead scalable, high-performance apps; develop robust APIs on AWS/Azure.
- Define technical vision and roadmaps for web-based data apps.
- Collaborate with lead engineers for alignment and platform evolution.
- Lead architecture decisions, code reviews, and ensure best practices.
- Coordinate across global teams with strong communication.
- Architect and optimize systems to handle growing data and users.
Skills
Education
Tools
Job description
Mastercard is seeking a hands-on Lead Software Engineer to drive architecture, design, and development of an advanced experimentation platform. You will mentor engineers, guide cross-functional teams, and champion scalable, cloud-native solutions leveraging AWS/Azure and Databricks.
You will collaborate across programs to align goals, define cross-cutting initiatives, and deliver enterprise-grade analytics capabilities.
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