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:
•\tArchitect and implement real-time (RT) and near-real-time (NRT) data engineering pipelines between Mastercard systems to support AI deployments.
•\tEnhance data engineering architecture to ensure reliability, maintainability, and scalability by improving deployment, monitoring, and fault tolerance.
•\tDevelop monitoring solutions to assess the health and performance of AI observability systems.
•\tLead technical decision-making, ensuring alignment with business goals and AI objectives.
•\tLead 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:
•\tImplement robust data security and compliance mechanisms, including anonymization and encryption, to handle sensitive data in retrieval systems.
•\tCollaborate with compliance teams to align retrieval infrastructure with Mastercard's data governance policies.
•\tEnsure the quality, accuracy, and integrity of datasets across the organization.
•\tEstablish monitoring frameworks to proactively address data pipeline issues and detect ML model drifts.
•\tImplement strategies for data versioning, lineage tracking, and auditability.
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3. Innovate in Data Solution Technologies:
•\tEnsure pipeline performance, monitoring and optimization balancing business and technology trade-offs.
•\tExplore and integrate emerging data strategies, AI model enhancements, and distributed systems for improved AI application performance.
•\tDrive the adoption of memory-based retrieval systems (e.g., Redis) and advanced AI infrastructure to enhance system scalability.
•\tArchitect solutions utilizing platform-as-a-service (PaaS), containerization technologies (e.g., Kubernetes, PCF), and cloud-native architectures.
•\tContribute to designing and implementing high-transaction volume financial systems with global scalability and extreme uptime requirements.
•\tDesign and develop global-scale back-end microservices using Java, Kafka, RabbitMQ, and related technologies.
•\tLead and Drive scalable data pipelines with Big Data technologies (e.g., Hadoop, Apache Spark, Spark SQL, Kafka, NiFi) for batch and incremental data loads.
•\tDeploy AI/ML pipelines in production environments using MLOps best practices.
•\tContinuously 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:
•\tWork closely with data scientists, analysts, and engineers to ensure seamless data accessibility and usability for AI applications.
•\tPartner with business stakeholders, product managers, and leadership teams to translate business requirements into technical solutions.
•\tCollaborate 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.
•\tProven expertise in leading and driving real-time data pipelines and large-scale distributed systems.
•\tHands-on experience with tools such as Hadoop, Apache Spark, Kafka, NiFi, and Big Data ecosystems.
•\tStrong knowledge of data security, compliance, and data governance standards.
•\tProficiency in programming languages such as Java, Python, or Scala.
•\tExperience with microservices architecture and messaging frameworks (e.g., Kafka, RabbitMQ).
•\tExtensive familiarity with cloud platforms (AWS) and container orchestration tools (Kubernetes, Docker).
•\tBackground in designing and managing high-performance, scalable and secure financial systems with global-scale architecture.
•\tNice 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:


•\tAbide by Mastercard’s security policies and practices.
•\tEnsure the confidentiality and integrity of the information being accessed.
•\tReport any suspected information security violation or breach, and
•\tComplete 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.