Vice President, Data Engineering

Mastercard • San Francisco, CA

1d

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. Title and Summary Vice President, Data Engineering Overview: Mastercard Services Technology team is seeking a Vice President of Data Engineering to lead the transformation of our enterprise data ecosystem and unlock the full value of Mastercard’s data assets. This role will drive innovation in how we manage, store, govern, and access large-scale data across both public cloud and on-premise environments, while establishing consistent engineering standards and principles across the Big Data landscape. This is a high-impact leadership role responsible for defining and delivering modern, scalable, and secure data and AI platforms across AWS and Azure. The scope includes platform strategy, enterprise governance, engineering excellence, and the establishment of best practices across global data and platform teams. This is a hands-on technical leadership role, with deep involvement in data engineering and architecture design and implementation. At the initial stage, this role will not have direct reports; however, as the platform and team evolve, it is expected to build and lead a team of approximately 5–10 engineers and platform specialists. We are looking for a leader who thrives in fast-paced environments, balances strategic vision with hands-on execution, and delivers measurable business impact through technology.

Requirements

• Proven experience as a Director or Vice President of Data Engineering, Data Architecture, or similar senior technical leadership roles.
• Strong hands-on experience in data engineering and architecture, with the ability to design and implement solutions directly when needed.
• Experience leading or scaling globally distributed engineering teams across multiple geographies.
• Deep expertise in AWS and Azure services, including S3, EC2, Lambda, Glue, Flink, Lake Formation, Azure Data Factory, Azure Fabric, Synapse, and Databricks.
• Strong experience building DevOps pipelines and infrastructure-as-code using Terraform, CloudFormation, ARM templates, Azure DevOps, or GitLab CI/CD.
• Strong understanding of cloud security architecture, including IAM design, encryption strategies, and governance frameworks.
• Experience with containerization and orchestration technologies such as Docker, Kubernetes, ECS, or AKS.
• Strong background in data engineering frameworks such as Spark, PySpark, and large-scale distributed ETL systems.
• Proven success delivering production-grade Lakehouse architectures using the medallion model.
• Strong leadership skills with demonstrated ability to influence senior stakeholders and drive cross-functional alignment.
• Experience with data governance platforms such as AWS Lake Formation or Azure Purview.
• Familiarity with observability and monitoring tools (CloudWatch, Azure Monitor, ELK, etc.)
• Experience with cloud cost optimization and financial accountability for large-scale platforms.
• Exposure to MLOps practices and integration of machine learning pipelines into data platforms.
• Strong experience working in Agile/Scrum environments.
• Strong executive communication and stakeholder management skills, with demonstrated experience engaging and influencing senior leadership and executive audiences, and the ability to convey complex ideas clearly to diverse audiences.
• Bachelor’s degree in a quantitative field such as Engineering, Mathematics, Computer Science, or related discipline, or equivalent practical experience.
• This role is not eligible for Mastercard’s work authorization sponsorship. As such, candidates must be eligible to work in the United States, now as well as in the future, without employer sponsorship.

Responsibilities

• Define and lead the architecture of end-to-end cloud-native data platforms, including lakehouse architectures built on S3, Azure Data Lake, Databricks, and related technologies.
• Provide technical leadership across data engineering, platform engineering, and DevOps organizations, guiding engineering leaders and cross-functional teams
• Act as a hands-on architect and engineer, contributing directly to the design, development, and implementation of core data platform components.
• Lead DevOps transformation initiatives, including CI/CD pipelines, infrastructure-as-code, and fully automated multi-cloud deployment models.
• Establish and enforce enterprise cloud security standards, including IAM, encryption, network security, and regulatory compliance (e.g., GDPR, HIPAA)
• Design and implement enterprise-grade data governance frameworks, including data cataloging, lineage, classification, and access control using tools such as AWS Lake Formation and Azure Purview.
• Architect and deliver scalable batch and streaming data pipelines supporting large-scale ETL/ELT workloads across data lakes and data warehouses.
• Implement and operationalize Lakehouse architectures using the medallion model (Bronze, Silver, Gold) across AWS services (Glue, Lake Formation, EMR, Athena) and Databricks.
• Translate complex business requirements into scalable, secure, and high-performance technical solutions in close partnership with product and engineering stakeholders.
• Drive operational excellence by improving performance, scalability, reliability, and cost efficiency of data platforms.
• Define and institutionalize architecture standards, engineering best practices, and operational frameworks across teams.
• Mentor engineers and future team members while building and scaling a high-performing team of 5–10 data engineers and platform engineers as the organization grows.

Benefits

• insurance (including medical, prescription drug, dental, vision, disability, life insurance)
• flexible spending account and health savings account
• paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave)
• 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire
• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Executive