Jobs / Canada / Mastercard International Incorporated
Lead Data Engineer (AI & Data Strategy)
Mastercard International Incorporated · 🇨🇦 Vancouver, Canada
Sponsorship verdict
No sponsorship evidence yet
No government record and no wording either way. Not a refusal — ask the recruiter.
- No government sponsor record hereNo government sponsor record covers this employer in this country.
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeCanada has no single salary bar: the employer usually needs a positive LMIA. Pay at or above the provincial median wage + 20% (e.g. C$36.92/h in Ontario) puts it in the high-wage stream. Source: https://www.canada.ca/en/employment-social-development/services/foreign-workers/median-wage.html, rules effective 2026-07-17.
- Confirmed live todayWhen a source last listed this job as open.
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Sponsor Radar — Mastercard International Incorporated
No government sponsor record covers this employer in this country.
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About the role
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 (AI & Data Strategy) Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. 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, Databric