Senior Data Engineer (Data Platforms)-1
Pune, Mahārāshtra, India
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingMastercard's Data Commercialization Platform team is looking for a Senior Data Engineer to build the platform's self-service experience and automated control layer.
This is a hands-on, end-to-end engineering role.
Build the self-service web experience for requesting data platform resources
Replace manual, multi-team request processes with governed automated workflows
Provision and govern cloud and lakehouse infrastructure for enterprise users
Extend the platform with data-intensive and AI-powered capabilities
From the employer’s posting
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.
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
The platform provisions and governs cloud and lakehouse infrastructure for enterprise users
and to extend it with data-intensive and AI-powered capabilities
Tools in this posting
- Java
- JavaScript
- Python
- TypeScript
- AWS
- Azure
- Databricks
- Delta Lake
- Iceberg
- Kafka
- Kubernetes
- NoSQL
- Snowflake
- Spark
- Terraform
- Trino
- Airflow
- PySpark
- React
Source — Tool mentions in context
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
Posting record
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- Live
- First seen by us
- Oct 5, 2026 · 20 days ago
- Recorded sightings
- 75
- Last seen by us
- Oct 25, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
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Job description
Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Senior Data Engineer (Data Platforms)-1Who 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 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.
Source details
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- Location & working pattern
Pune, Mahārāshtra, India
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