Job Title:

Senior Data Engineer

Overview:

Overview
The Security Solutions Data Science team is responsible for creating Artificial Intelligence (AI) and Machine Learning (ML) models backing its flagship product. The models generated are production ready and created to back specific products in Mastercard's authentication and authorization networks. The Data Science team is also responsible for developing automated processes for creating models covering all modeling steps, from data extraction up to delivery. In addition, the processes must be designed to scale, to be repeatable, resilient, and industrialized.

Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution.

You will be joining a team of Data Scientists and engineers working on innovative AI and ML fraud detection. Our innovative cross-channel AI solutions are applied in Fortune 500 companies in industries such as fin-tech and payments processing. We are pursuing a highly motivated individual with strong problem-solving skills to take on the challenge of structuring and engineering data and cutting-edge AI model evaluation and reporting processes.

Role
As a Senior Data Engineer, you will:
• Collaborate closely with data scientists to understand the current modeling pipeline and identify optimization opportunities.
• Integrate and manage data from various sources and storage systems, creating processes and pipelines to produce cohesive datasets for analysis and modeling.
• Develop data pipelines to automate repetitive tasks within data science and data engineering.
• Assist the deployment team to deploy and validate production artifacts.
• Identify patterns and innovative solutions in existing spaces, consistently seeking opportunities to simplify, automate tasks, and build reusable components for multiple use cases and teams.
• Create data products that are well-modeled, thoroughly documented, and easy to understand and maintain.

All About You

Essential Skills:
• Experience working in cross-functional teams or across different teams to solve complex problems.
• Comfortable working in environments with undefined or loose requirements.
• Demonstrated ability to structure ETL/ELT pipelines into reusable, maintainable, and configuration-driven components.
• Proficient in writing unit and integration tests for data transformations; automated validation.
• Adheres to Git best practices, automated linting/testing pipelines, and clear technical documentation.
• Good knowledge of Linux / Bash environment
• Experience in the following platforms: Python, Pyspark, Airflow, CI/CD, JIRA, Hadoop, SQL, Databricks
• Good communication skills
• Highly skilled problem solver
• Exhibits a high degree of initiative
• At least an undergraduate degree in CS, or a STEM related field

Nice to have:
• Graduate degree in CS, Data Science, Machine Learning, AI or a related STEM field
• Experience building AI/ML feature pipelines
• Experience in with data engineering on petabyte scale data
• Understands and implements methods to evaluate own work and others for error
• Loves working with error-prone, messy, disparate, unstructured data
• Experience in data analytics
• Experience designing scalable, reliable, and metadata-driven data pipelines and architectures, with strong understanding of data modeling, orchestration, and governance.

To find US Salary Ranges, visit People Place. Under the Compensation tab, select "Salary Structures." Within the text of "Salary Structures," click on the link "salary structures 2025," through which you will be able to access the salary ranges for each Mastercard job family. For more information regarding US benefits, visit People Place and review the Benefits tab and the Time Off & Leave tab.