As a Lead Data Engineer, you will optimize modeling pipelines, manage data integration, and develop automated data processes while mentoring junior engineers.
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
Lead Data Engineer
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.
As a Lead Data Engineer, you will:• Lead collaboration with data scientists to understand the existing modeling pipeline and identify optimization opportunities.• Oversee the integration and management of data from various sources and storage systems, establishing processes and pipelines to produce cohesive datasets for analysis and modeling.• Design and develop data pipelines to automate repetitive tasks within data science and data engineering.• Demonstrated experience leading cross-functional teams or working across different teams to solve complex problems.• Partner with software engineering teams 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.• Comfortable leading projects in environments with undefined or loose requirements.• Mentor junior data engineers
All About You• Good knowledge of Linux / Bash environment• Experience in the following platforms: Python, Pyspark, Airflow, CI/CD, JIRA, Hadoop, SQL, Databricks, Atlan• 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• Data Engineering Experience• Experience with Java• Experience with Jenkins• 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
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 role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact [email protected] and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.
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:
Pay Ranges
Vancouver, Canada: $127,000 - $203,000 CAD
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
Lead Data Engineer
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.
As a Lead Data Engineer, you will:• Lead collaboration with data scientists to understand the existing modeling pipeline and identify optimization opportunities.• Oversee the integration and management of data from various sources and storage systems, establishing processes and pipelines to produce cohesive datasets for analysis and modeling.• Design and develop data pipelines to automate repetitive tasks within data science and data engineering.• Demonstrated experience leading cross-functional teams or working across different teams to solve complex problems.• Partner with software engineering teams 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.• Comfortable leading projects in environments with undefined or loose requirements.• Mentor junior data engineers
All About You• Good knowledge of Linux / Bash environment• Experience in the following platforms: Python, Pyspark, Airflow, CI/CD, JIRA, Hadoop, SQL, Databricks, Atlan• 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• Data Engineering Experience• Experience with Java• Experience with Jenkins• 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
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 role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact [email protected] and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.
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.
Pay Ranges
Vancouver, Canada: $127,000 - $203,000 CAD
Top Skills
Airflow
Atlan
Ci/Cd
Databricks
Hadoop
JIRA
Pyspark
Python
SQL
Mastercard Boston, Massachusetts, USA Office
Our downtown Boston office is strategically located in the financial district, a short walk from South Station - one of the busiest transportation center in New England - and the Seaport District - a bustling, waterfront neighborhood and the tech hub of the city.
Similar Jobs at Mastercard
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Lead the development and operational excellence of Mastercard's AI platform, focusing on architecture, engineering teams, and scalable AI solutions.
Top Skills:
AWSAzureDockerFastapiFlaskGCPGitGrafanaKubernetesNode.jsPrometheusPythonTerraform
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
As a Data Scientist I, you will analyze complex data, develop machine learning models, and innovate on product ideas to enhance digital transaction security.
Top Skills:
AWSGCPPysparkPython
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
The Senior Product Manager oversees the Mastercard Send program, collaborates with various teams, addresses performance issues, and ensures customer satisfaction through data-driven insights and relationship management.
Top Skills:
ExcelPowerPoint
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories

