Senior Data Engineer (Data Platforms)

Overview

Mastercard is seeking a Senior Data Engineer to build a self-service experience and automated control layer for its Data Commercialization Platform. This hands-on, end-to-end role spans user-facing web experiences, data, APIs and cloud layers in a multi-cloud environment.

What you'll do

• Build the platform's self-service experience and automated control layer.
• Replace manual, multi-team request processes with a governed, intuitive experience.
• Extend the platform with data-intensive and AI-powered capabilities.
• Provision and govern cloud and lakehouse infrastructure for enterprise users.
• Build back-end services in Java, including Core Java, Spring Boot and REST APIs.
• Build web experiences in React and TypeScript/JavaScript with attention to responsive design, accessibility and performance.
• Design workflow orchestration platforms, automation frameworks or long-running stateful processes.
• Implement retries, idempotency and reconciliation.
• Integrate with external systems through REST or GraphQL APIs.
• Design and operate scalable solutions across UI, API, data and cloud layers.
• Evaluate technical trade-offs and contribute to architecture and design discussions.
• Explain complex solutions to engineering, security, platform and business stakeholders.
• Use AI coding assistants and modern developer productivity tools to speed up delivery and improve code quality.
• Abide by Mastercard’s security policies and practices.
• Ensure the confidentiality and integrity of accessed information.
• Report suspected information security violations or breaches.
• Complete periodic mandatory security training in accordance with Mastercard’s guidelines.

What you'll need

• Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
• 6+ years of experience building scalable, reliable data platforms and software in agile environments.
• Experience using distributed systems, microservices and RESTful APIs.
• Experience building and operating modern data and lakehouse platforms using Python, Spark/PySpark, 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.
• Deep hands-on cloud engineering experience on AWS and/or Azure.
• Experience with Kubernetes, networking, identity and access management, storage, security, infrastructure-as-code, CI/CD, observability and cost optimization.
• Experience with Terraform, CloudFormation, or CDK.
• Experience with relational and NoSQL databases, query optimization, caching, asynchronous processing and application scalability patterns.
• 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.

Nice to have

• Experience with streaming and distributed data technologies such as Kafka, Flink, Trino, EMR, or Snowflake.
• Exposure to AI-powered development, including LLM-based applications, retrieval-augmented generation (RAG), agentic frameworks, and evaluation techniques.

Details

• Location: Pune, India.