Leads data engineering for cyber analytics by designing pipelines, ETL processes, storage, graph databases, and data models. Partners with data scientists and technology teams to integrate ML and AI solutions, manage production deployments, and build cohesive analytical datasets. Oversees and develops a team of data engineers, manages priorities, and collaborates with technical and business stakeholders.
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
Director, Data Engineering
Overview:
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. The Director, Data Engineering for Cyber Analytics will be a key contributor in helping Mastercard develop and deliver actionable insights and products to mitigate cyber vulnerabilities across the Mastercard ecosystem.
Role:
• Design, develop, test, deploy, maintain, and improve data storage, pipelines, and ETL processes.• Lead the design and build of graph database solutions and data models that support cyber analytics use cases.• Partner with data scientists to understand existing ML and AI applications, identify optimization opportunities, and craft processes and solutions that streamline data engineering integration.• Oversee the integration and management of data from various sources and storage systems to produce cohesive datasets for analysis and modeling.• Partner with software engineering, IT, Info Sec, and infrastructure teams to deploy and validate production artifacts.• Lead, develop, and grow a team of highly skilled data engineers.
All About You:
• Strong data engineering skills, including building data pipelines and infrastructure for ML and AI applications, with a solid understanding of ML and AI concepts to build solutions together with data scientists.• Proficiency in graph databases and graph modeling techniques.• Proficiency in Databricks, Spark, and AWS, with working knowledge of on-prem distributions (Apache, Hadoop, Oracle).• Skilled in databases and big data tools such as Hive, Impala, OOZIE, Airflow, and NIFI, with working knowledge of Shell scripting and Linux/Unix systems.• Strong computer science fundamentals in object-oriented design, data structures, algorithm design, and complexity analysis.• Proven ability to lead and develop a team of data engineers.• Skilled at delegating, organizing, and motivating a team, and at prioritizing competing requests across multi-person projects.• Strong stakeholder management, with the ability to build trusted relationships across technical and business partners.• Strong problem-solving skills, with the ability to break down ambiguous problems, propose solutions, and implement them with cross-functional teams.• Clear, persuasive communication with both technical and non-technical audiences, in writing and verbally.• Curiosity and adaptability, with the ability to learn new domains quickly and stay open to alternative ideas.
Preferred Skills:
• A degree in a technical field such as Mathematics, Statistics, Physics, Engineering, Cybersecurity, or Computer Science, or equivalent skills gained through hands-on work.• Knowledge of the payments, cyber, and/or fraud domains.• Knowledge of web crawling and scraping.• Exposure to agentic AI.
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:
In line with Mastercard's total compensation philosophy and assuming that the job will be performed in Canada, the successful candidate will be offered a competitive pay based on location, experience and other qualifications for the role and may be eligible to participate in a discretionary annual incentive program. This posting reflects one or more current openings on our team.
Pay Ranges
Toronto, Canada: $154,000 - $247,000 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
Director, Data Engineering
Overview:
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. The Director, Data Engineering for Cyber Analytics will be a key contributor in helping Mastercard develop and deliver actionable insights and products to mitigate cyber vulnerabilities across the Mastercard ecosystem.
Role:
• Design, develop, test, deploy, maintain, and improve data storage, pipelines, and ETL processes.• Lead the design and build of graph database solutions and data models that support cyber analytics use cases.• Partner with data scientists to understand existing ML and AI applications, identify optimization opportunities, and craft processes and solutions that streamline data engineering integration.• Oversee the integration and management of data from various sources and storage systems to produce cohesive datasets for analysis and modeling.• Partner with software engineering, IT, Info Sec, and infrastructure teams to deploy and validate production artifacts.• Lead, develop, and grow a team of highly skilled data engineers.
All About You:
• Strong data engineering skills, including building data pipelines and infrastructure for ML and AI applications, with a solid understanding of ML and AI concepts to build solutions together with data scientists.• Proficiency in graph databases and graph modeling techniques.• Proficiency in Databricks, Spark, and AWS, with working knowledge of on-prem distributions (Apache, Hadoop, Oracle).• Skilled in databases and big data tools such as Hive, Impala, OOZIE, Airflow, and NIFI, with working knowledge of Shell scripting and Linux/Unix systems.• Strong computer science fundamentals in object-oriented design, data structures, algorithm design, and complexity analysis.• Proven ability to lead and develop a team of data engineers.• Skilled at delegating, organizing, and motivating a team, and at prioritizing competing requests across multi-person projects.• Strong stakeholder management, with the ability to build trusted relationships across technical and business partners.• Strong problem-solving skills, with the ability to break down ambiguous problems, propose solutions, and implement them with cross-functional teams.• Clear, persuasive communication with both technical and non-technical audiences, in writing and verbally.• Curiosity and adaptability, with the ability to learn new domains quickly and stay open to alternative ideas.
Preferred Skills:
• A degree in a technical field such as Mathematics, Statistics, Physics, Engineering, Cybersecurity, or Computer Science, or equivalent skills gained through hands-on work.• Knowledge of the payments, cyber, and/or fraud domains.• Knowledge of web crawling and scraping.• Exposure to agentic AI.
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.
In line with Mastercard's total compensation philosophy and assuming that the job will be performed in Canada, the successful candidate will be offered a competitive pay based on location, experience and other qualifications for the role and may be eligible to participate in a discretionary annual incentive program. This posting reflects one or more current openings on our team.
Pay Ranges
Toronto, Canada: $154,000 - $247,000 CAD
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