Match Score
Against your primary resumeLogin to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Protocol Intelligence
Data-driven signals on your job's competitivenessLog in to see why each signal reads the way it does.
Job Description
Structured overview of role & requirementsAbout This Role
Build and enhance Mastercard's Data Commercialization Platform focusing on a self-service experience and automated control layer for cloud and lakehouse infrastructure.
Own end-to-end engineering from user-facing web (React, TypeScript) to backend services (Java, Spring Boot) and multi-cloud data platform layers including APIs, compute, networking, and security.
Design and implement scalable, secure, and reliable data platform solutions with automation, workflow orchestration (e.g. Apache Airflow), and integration of AI-powered capabilities.
Minimum Requirements
Bachelor's degree in Computer Science or related technical field or equivalent experience.
6+ years experience building scalable, reliable data platforms and software in agile environments.
Proficiency in modern cloud data platforms (AWS/Azure), data engineering tools (Python, Spark/PySpark, Databricks), backend (Java, Spring Boot), frontend (React, TypeScript) development, and infrastructure-as-code (Terraform, CloudFormation, CDK).
Experience with workflow orchestration, REST/GraphQL APIs, security, identity and access management, and application scalability patterns.
Ideal Candidate Profile
Experienced in designing and operating multi-cloud data platforms with hands-on skills across the full stack including UI, backend services, and cloud infrastructure.
Comfortable contributing to architecture and design decisions, explaining complex technical solutions to diverse stakeholders including engineering, security, and business teams.
Familiar with integrating AI-powered features and advanced data technologies such as lakehouse architectures, and automation frameworks for enterprise-grade systems.