Senior Data Engineer (Data Platforms)-1

Build and own Mastercard's Data Commercialization Platform self-service experience and automated control layer to replace manual multi-team request processes with governed, intuitive workflows.

Develop end-to-end solutions spanning user-facing web experience, backend APIs, and cloud infrastructure in a multi-cloud environment provisioning and governing cloud and lakehouse infrastructure.

Ensure scalable, secure, and reliable platform operation with deep expertise in cloud compute, networking, identity, storage, security, and infrastructure automation.

Bachelor's degree in Computer Science or related technical field (or equivalent practical experience).

6+ years experience building scalable, reliable data platforms and software in agile environments with distributed systems, microservices, and RESTful APIs.

Strong hands-on experience with Python, Spark/PySpark, Databricks, Apache Airflow; backend services in Java (Spring Boot, REST APIs); frontend development with React and TypeScript/JavaScript.

Deep cloud engineering experience on AWS and/or Azure including Kubernetes, networking, identity/access management, storage, security, infrastructure-as-code (Terraform, CloudFormation, or CDK), CI/CD, observability, and cost optimization.

Experienced in designing and operating modern data and lakehouse platforms (Delta Lake, Apache Iceberg, Unity Catalog) with strong end-to-end application development skills spanning front-end, back-end, and cloud layers.

Comfortable working in multi-cloud environments and automating cloud infrastructure provisioning and governance for enterprise-scale data platforms.

Ability to design workflow orchestration and automation frameworks handling retries, idempotency, reconciliation, and integration with external APIs, alongside evaluating technical trade-offs and communicating complex solutions to diverse stakeholders.