Senior Data Engineer (Data Platforms)

Engg; Pune District; On-site; INR 2,400,000 - 4,800,000; Full time

Job summary

Mastercard in Pune, India, seeks a Senior Data Engineer (Data Platforms) to build and govern a self-service platform across multi-cloud environments. The role focuses on end-to-end engineering from the user-facing interface to data, API, and cloud layers, delivering scalable and secure solutions.

Responsibilities include developing with Python, Spark, and Databricks, designing streaming and batch data pipelines, and collaborating with cross-functional teams to ensure performance and reliability.

Qualifications

• Bachelor's degree in CS or related field.
• 6+ years building scalable data platforms in agile environments.
• Experience with Python, Spark/PySpark, Databricks, Unity Catalog, Iceberg/Delta.
• Backend and frontend skills: Java Spring Boot REST APIs and React/TypeScript.
• Cloud engineering on AWS or Azure, including Kubernetes, IAM, storage and security.
• Experience designing workflow orchestration and integrations via REST/GraphQL APIs.
• Experience with relational and NoSQL databases, optimization and caching.
• Experience with streaming tech like Kafka, Flink, Trino, EMR, or Snowflake is a plus.
• Exposure to AI-powered dev including LLM/RAG and agents.
• Strong secure coding, observability and troubleshooting across UI, API, data, and cloud layers.
• Ability to evaluate trade-offs and explain complex solutions to stakeholders.
• Experience using AI coding assistants and developer productivity tools.

Skills

Distributed systems

Microservices

REST APIs

Agile methodologies

Secure coding

Performance optimization

Cloud computing

SQL & NoSQL

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks

Unity Catalog

Apache Iceberg

Delta Lake

Airflow

AWS / Azure

Kubernetes

Terraform

CI/CD pipelines

Job description

Title and Summary

Senior Data Engineer (Data Platforms) Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Our decency quotient, or DQ, drives our culture and everything we do. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

About the Role

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/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. 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 TypeScript/JavaScript, 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, CloudFormation, 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 GraphQL APIs.
• Experience with relational and NoSQL 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.