M
Mastercard
Data Engineer

Lead Data Engineer (Data Platforms)

On-siteSeniorData EngineerJust posted
Role summaryAI-generated

Lead Data Engineer at Mastercard will design and scale cloud-based data and analytics solutions for the Data Commercialization Platform, focusing on BI, data engineering, and platform capabilities. The role requires building robust data pipelines, leveraging Spark and Databricks, and collaborating with cross-functional teams to deliver insights that drive commercial decisions.

Skills required

About this role

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

Lead Data Engineer (Data Platforms)

Role Summary

We are looking for a Lead Software Engineer to design, build, and scale cloud-based data and analytics solutions within Mastercard’s Data Commercialization Platform (DCP).
This role focuses on delivering Business Intelligence (BI), data engineering, and platform capabilities using Databricks, Snowflake, AWS, and Azure, while ensuring strong governance, scalability, and interoperability across multi-cloud environments.
The ideal candidate will combine hands-on engineering expertise.


Key Responsibilities

Architecture & Development
Design and develop cloud-native data and BI solutions using Databricks and Snowflake on AWS.
Build scalable, high-performance data pipelines and analytics frameworks supporting enterprise data products.
Drive implementation of multi-cloud architecture leveraging AWS and Azure (Azure Databricks, ADLS Gen2).

Platform Engineering & Integration
Enable seamless integration across Databricks, Snowflake, AWS services, and Azure services.
Build and maintain CI/CD pipelines, automation frameworks, and infrastructure-as-code for data platform provisioning.
Implement secure and governed access patterns including RBAC, service principals, and enterprise identity integration.
Support data platform interoperability across multiple compute engines and cloud providers.


Required Qualifications
8+ years of experience in software engineering / data engineering / platform engineering
Strong hands-on experience with:
Databricks (AWS / Azure)
Snowflake
AWS services (S3, Glue, EMR, IAM, etc.)
Experience building cloud-based data platforms or BI/analytics solutions
Strong knowledge of distributed systems, data processing, and scalable architectures
Experience with CI/CD, Infrastructure as Code, and automation
Proven ability to lead technical design and mentor engineers
Preferred Qualifications
Experience with Azure (Azure Databricks, ADLS Gen2, AKS)
Knowledge of open data formats (Delta Lake, Apache Iceberg)
Experience with data governance frameworks and access control models
Exposure to multi-cloud architecture and cross-platform interoperability
Understanding of FinOps, cost optimization, and platform observability

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.




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