Senior Data Engineer

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

Senior Data Engineer

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:

• Write high-quality, performant, clean, and testable code that adheres to best practices and coding standards, ensuring maintainability and scalability.
• Design, develop, and maintain data pipelines that automate tasks within data science and data engineering, enhancing workflow efficiency.
• Work in cross-functional teams and across different business units to tackle complex problems, fostering a collaborative and innovative environment.
• Assist in deploying and validating production artifacts, ensuring seamless integration and functionality.
• Identify opportunities to simplify and automate tasks, building reusable components that serve multiple use cases and teams.
• Create data assets that are well-modeled, thoroughly documented, and easy to understand and maintain, contributing to a robust data infrastructure.
• Develop functional requirements in complex environments, ensuring solutions meet business needs and technical specifications.
• Utilize advanced big data platforms and technologies to handle data at petabyte scale, pushing the boundaries of what is possible in data engineering.

All About You
Essential Skills to be successful:

• Proven experience in Python, PySpark and SQL, showcasing the ability to write clean, readable, and maintainable code.
• Hands-on knowledge of any big data engine, with a preference for Spark, demonstrating proficiency in managing large-scale data.
• Strong experience with CI/CD tools such as Git and Jenkins, ensuring efficient and reliable code deployment.
• Excellent communication skills, enabling effective collaboration and knowledge sharing.
• Highly skilled in problem-solving, capable of addressing complex challenges with innovative solutions.
• Exhibits a high degree of initiative and a strong curiosity, with a desire to continuously learn and grow.
• Strong understanding of Agile methodologies, with the ability to drive iterative delivery and cross-team collaboration.
• Strong communicator with the ability to explain complex concepts to both technical and non-technical audiences, and to influence stakeholders across product, engineering, and acquisition teams.
• Bachelor’s degree in Computer Science, Data Analytics, Mathematics, Software Engineering, or a related field or equivalent practical experience.

Nice to have:

• Experience with Airflow, Databricks, Hadoop
• Experience in with data engineering on petabyte scale data
• Passion of Machine Learning
• Comfortable with pioneering new technology

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Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the r