**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**
Principal Data Engineer
Overview
We are seeking a highly experienced and strategic Principal Data Engineer to lead the data engineering architecture and implementation for our enterprise-wide Finance Modernization Initiative. This role will drive the design, development, and governance of modern data platforms and scalable engineering frameworks that support financial transformation, analytics, regulatory reporting, and operational excellence.
The ideal candidate brings deep expertise in modern data engineering technologies including Apache Spark, Apache Iceberg, and AWS cloud services, along with strong exposure to software engineering best practices, API development, event-driven architectures, Apache Kafka, and enterprise data integration patterns.
Key Responsibilities
Platform Architecture & Design
• Lead the architecture, design, and implementation of scalable enterprise data platforms supporting finance modernization initiatives.
• Design modern data lakehouse architectures leveraging Apache Spark, Apache Iceberg, and cloud-native AWS services.
• Define and establish enterprise-wide data engineering frameworks, standards, reusable patterns, and best practices.
• Drive data platform modernization strategies including batch, streaming, and real-time data processing solutions.
Engineering Leadership
• Mentor and guide senior engineers and technical teams across the organization.
• Lead technical discussions, architecture reviews, and strategic modernization initiatives.
• Apply modern software engineering principles, CI/CD practices, and DevOps methodologies within data engineering environments.
• Collaborate with product owners, finance leaders, architects, and cross-functional engineering teams.
Integration & APIs
• Design and develop robust APIs and microservices for enterprise data access and integrations.
• Implement event-driven and streaming architectures using Apache Kafka or equivalent technologies.
• Establish data governance frameworks, lineage tracking, and quality standards across the platform.
• Ensure compliance with regulatory reporting requirements and financial data governance standards.
All About you
• 12+ years of experience in data engineering, data platform development, or related technical roles.
• Proven track record of architecting and delivering large-scale enterprise data platforms in a principal or lead capacity.
• Knowledge of data mesh or data product architectures in enterprise settings.
• Expert-level proficiency in Apache Spark (PySpark) for large-scale data processing.
• Deep hands-on experience with Apache Iceberg or similar open table formats
• Experience designing and implementing streaming architectures using Apache Kafka
• Experience designing and building REST APIs and microservices for enterprise data access.
• Solid understanding of CI/CD pipelines, infrastructure-as-code and DevOps practices.
• Experience with data governance, data quality frameworks, and metadata management tools.
**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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