Executive Vice President, Data Platforms

About the position

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. We are seeking an innovative and highly technical Executive to lead the strategy, design, implementation, and optimization of data engineering solutions for our SaaS products. This hands-on leadership role is crucial in shaping the data architecture, platforms, and pipelines that power our customer-facing applications, customer analytics and AI enabled products/services. The ideal candidate will have deep expertise in cloud-native data platforms, SaaS product data strategies, and advanced engineering practices, coupled with strong leadership skills to drive the growth of a scalable, data-centric SaaS ecosystem.

Responsibilities

• Responsible for the strategy and architecture development of all cloud capabilities for our current and future SaaS and AI products in Services.
• Internally influence/collaborate with stakeholders across engineering, product management, marketing, and operations to align data strategies with business goals.
• Advocate for and implement modern data architecture principles, such as data lakes, data warehouses, and data meshes, to drive innovation and growth.
• Define and execute the company’s data engineering strategy, tailored to meet the unique requirements of SaaS products, ensuring scalability, security, and reliability.

Requirements

• Deep executive experience in data engineering, with at least 7 years in leadership roles managing large-scale, SaaS-focused data platforms.
• Proven experience designing and managing data engineering solutions for SaaS products, focusing on multi-tenant architectures and customer analytics.
• Deep understanding of SaaS product lifecycle data, including usage tracking, subscription analytics, and customer segmentation.
• Extensive hands-on experience with AWS, Azure, or Google Cloud Platform, including services like Redshift, BigQuery, or Azure Synapse.
• Strong knowledge of cloud-native storage solutions, real-time data streaming, and serverless compute platforms.
• Advanced skills in data modeling, schema design, and handling structured and unstructured data for SaaS applications.
• Expertise in tools like Apache Kafka, Apache Spark, and real-time processing frameworks.
• Proficiency in programming languages such as Python, Java, or Scala, and advanced SQL skills.

Nice-to-haves

• Certifications in AWS, Azure, or Google Cloud platforms (e.g., AWS Certified Solutions Architect, Google Professional Data Engineer).
• Experience with data governance tools like Collibra, Alation, or similar platforms.
• Knowledge of data privacy and security standards specific to SaaS, such as SOC 2 compliance.

Benefits

• Insurance (including medical, prescription drug, dental, vision, disability, life insurance).
• Flexible spending account and health savings account.
• Paid leaves (including 16 weeks new parent leave, up to 20 paid days bereavement leave).
• 10 annual paid sick days.
• 10 or more annual paid vacation days based on level.
• 5 personal days.
• 10 annual paid U.S. observed holidays.
• 401k with a best-in-class company match.
• Deferred compensation for eligible roles.
• Fitness reimbursement or on-site fitness facilities.
• Eligibility for tuition reimbursement.
• Gender-inclusive benefits.