Principal Data Engineer - AI Products

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 - AI Products

Principal Data Engineer : AI Products
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
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. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential.
Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.
Roles and Responsibilities:
1. Design & Develop Scalable Retrieval Infrastructure:
• Architect and implement real-time (RT) and near-real-time (NRT) data engineering pipelines between Mastercard systems to support AI deployments.
• Enhance data engineering architecture to ensure reliability, maintainability, and scalability by improving deployment, monitoring, and fault tolerance.
• Develop monitoring solutions to assess the health and performance of AI observability systems.
• Lead technical decision-making, ensuring alignment with business goals and AI objectives.
• Lead and Drive scalable and efficient ETL/ELT processes to transform raw data into actionable insights and AI-driven velocities.
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2. Ensure Data Security, Privacy, and Compliance:
• Implement robust data security and compliance mechanisms, including anonymization and encryption, to handle sensitive data in retrieval systems.
• Collaborate with compliance teams to align retrieval infrastructure with Mastercard's data governance policies.
• Ensure the quality, accuracy, and integrity of datasets across the organization.
• Establish monitoring frameworks to proactively address data pipeline issues and detect ML model drifts.
• Implement strategies for data versioning, lineage tracking, and auditability.
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3. Innovate in Data Solution Technologies:
• Ensure pipeline performance, monitoring and optimization balancing business and technology trade-offs.
• Explore and integrate emerging data strategies, AI model enhancements, and distributed systems for improved AI application performance.
• Drive the adoption of memory-based retrieval systems (e.g., Redis) and advanced AI infrastructure to enhance system scalability.
• Architect solutions utilizing platform-as-a-service (PaaS), containerization technologies (e.g., Kubernetes, PCF), and cloud-native architectures.
• Contribute to designing and implementing high-transaction volume financial systems with global scalability and extreme uptime requirements.
• Design and develop global-scale back-end microservices using Java, Kafka, RabbitMQ, and related technologies.
• Lead and Drive scalable data pipelines with Big Data technologies (e.g., Hadoop, Apache Spark, Spark SQL, Kafka, NiFi) for batch and incremental data loads.
• Deploy AI/ML pipelines in production environments using MLOps best practices.
• Continuously improve data systems to meet the evolving needs of AI applications and business objectives.
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4. Collaborate with AI and Product Engineering Teams:
• Work closely with data scientists, analysts, and engineers to ensure seamless data accessibility and usability for AI applications.
• Partner with business stakeholders, product managers, and leadership teams to translate business requirements into technical solutions.
• Collaborate with software engineers and architects to integrate data platforms with Mastercard’s enterprise systems.
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Required Skills & Qualifications: The number of years of experience is flexible if all other requirements are met.
• Proven expertise in leading and driving real-time data pipelines and large-scale distributed systems.
• Hands-on experience with tools such as Hadoop, Apache Spark, Kafka, NiFi, and Big Data ecosystems.
• Strong knowledge of data security, compliance, and data governance standards.
• Proficiency in programming languages such as Java, Python, or Scala.
• Experience with microservices architecture and messaging frameworks (e.g., Kafka, RabbitMQ).
• Extensive familiarity with cloud platforms (AWS) and container orchestration tools (Kubernetes, Docker).
• Background in designing and managing high-performance, scalable and secure financial systems with global-scale architecture.
• Nice to have experience in MLOps workflows and deploying machine learning models in production environments.
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.

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.