Senior Data Engineer (Data Platforms)

Mastercard's Data Commercialization Platform team is looking for a Senior Data Engineer to build the platform's self-service experience and automated control layer. The goal is to replace manual, multi-team request processes with a governed, intuitive experience, and to extend it with data-intensive and AI-powered capabilities. This is a hands-on, end-to-end engineering role. It covers everything from the user-facing web experience down to the data, API and cloud layers underneath, in a multi-cloud environment. The platform provisions and governs cloud and lakehouse infrastructure for enterprise users. The role requires deep expertise in cloud data platforms, including compute, networking, identity, storage and security. Candidates must understand how these services work together to deliver scalable, secure and reliable solutions. All About You: Bachelor's degree in Computer Science or a related technical field (or equivalent practical experience). You have 6+ years of experience building scalable, reliable data platforms and software in agile environments, using distributed systems, microservices and RESTful APIs. Experience building and operating modern data and lakehouse platforms using Python, Spark/Py Spark, Databricks, Unity Catalog, Apache Iceberg or Delta Lake, object storage, and workflow orchestration tools such as Apache Airflow. Strong end-to-end application development skills. This means building back-end services in Java (Core Java, Spring Boot, REST APIs) and the web experiences on top of them in React and Type Script/Java Script, with attention to responsive design, accessibility and performance. Deep hands-on cloud engineering experience on AWS and/or Azure, including Kubernetes, networking, identity and access management, storage, security, infrastructure-as-code (Terraform, Cloud Formation, or CDK), CI/CD, observability, and cost optimization. Experience designing workflow orchestration platforms, automation frameworks, or long-running stateful processes. This includes retries, idempotency, reconciliation, and integration with external systems through REST or Graph QL APIs. Experience with relational and No SQL databases, query optimization, caching, asynchronous processing, and application scalability patterns. Experience with streaming and distributed data technologies such as Kafka, Flink, Trino, EMR, or Snowflake is a plus. Exposure to AI-powered development, including LLM-based applications, retrieval-augmented generation (RAG), agentic frameworks, and evaluation techniques. Strong engineering fundamentals, including secure coding practices, access control models, automated testing, observability, and troubleshooting across UI, API, data, and cloud layers. Ability to evaluate technical trade-offs, contribute to architecture and design discussions, and explain complex solutions to engineering, security, platform and business stakeholders. Experience using AI coding assistants and modern developer productivity tools to speed up delivery and improve code quality. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. Everyone wants easier ways to pay; we invent them. Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. Retailers want to fight fraud; we provide the tools.