Sr Data Engineer
Full-time
Mastercard
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
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
• 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 About You
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
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. RoleAs 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
• 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 About You
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.
Vacancy posted 22 days ago
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