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
Sr Data Engineer
Overview
The AI Innovation at Scale team is seeking a highly motivated and detail-oriented Quality Assurance Engineer to join our team. This role is critical in ensuring the delivery of high-quality products by assessing requirements, identifying issues, and implementing effective testing strategies. The ideal candidate is curious, detail-oriented, technically skilled, and thrives in a collaborative environment. You will play a key role in improving quality management and continuous improvement.
Role As a Senior AI Engineer, you will:
Be an integral part of a creative and innovative team, contributing to collaborative projects and sharing insights to drive engineering and data science excellence
Work with cutting-edge big data platforms (e.g., Databricks, Apache Spark) at petabyte scale, pushing the boundaries of data processing and model enablement
Partner closely with Data Science teams to enable seamless R&D, scale models, features, and experimentations into reliable systems
Support the deployment of model features and model artifacts, ensuring seamless integration into production environments and downstream decisioning systems
Write clean, testable, and maintainable code, ensuring solutions are robust, efficient, and production-grade
Design, build, and maintain data pipelines that integrate multiple data sources to support a unified merchant registry and trust profile, enabling richer datasets and unlocking new opportunities for innovation
Collaborate with data operations and governance teams to move and manage data in compliance with security standards, policies, and regulatory requirements
Contribute to the design and evolution of scalable, entity-centric data models that support merchant identity resolution and longitudinal profiling
Automate and maintain data workflows in distributed environments, improving reliability and operational efficiency
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Analyze and optimize ETL/ELT processes to support high-performance data access and model execution
Implement testing frameworks and monitoring capabilities to ensure production solutions are reliable, observable, and continuously improving
Support incident response, debugging, and performance tuning of production AI/ML systems
Essential Skills to be successful:
Proven track record of self-directed learning, demonstrating the ability to acquire new skills and knowledge independently
Strong independent research skills and resourcefulness, enabling you to find solutions and innovate in data engineering
Strong understanding of data pipelines and end-to-end ML model development workflows, with exposure to entity-centric data systems
Experience with Python and SQL, showcasing the ability to write clean, readable, and maintainable code
Experience with big data technologies (e.g., Spark, distributed compute frameworks)
Hands-on experience with cloud platforms such as Databricks, AWS, or GCP
Critical thinking and a drive to produce high-quality work, ensuring all solutions meet rigorous standards
Strong communication skills, enabling effective collaboration with team members and stakeholders
Experience collaborating across data science, engineering, and governance teams
Ability and interest in problem-solving, with a proactive approach to tackling challenges
Openness to learn and apply new technologies, staying current with industry trends and advancements
Familiarity with Agile methodologies, with the ability to drive iterative delivery and cross-team collaboration
Bachelor’s degree in Computer Science, Data Analytics, Mathematics, Software Engineering, or a related field or equivalent practical experience
Contributions to platform standardization, reusability, and shared tooling across teams
Nice to Have
Experience working in hybrid environments (cloud and on-premises)
Familiarity with ML lifecycle and CI/CD practices for data and ML workflows
Experience with data governance, lineage, and metadata management
Exposure to batch, streaming, or real-time data pipelines and production ML monitoring/observability
Experience supporting high-scale production systems in merchant, fraud, or payment domains
Understanding of security, compliance, and handling sensitive data
Experience designing scalable databases and data models such as business registries
Experience with database updates and maintenance
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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