Senior Principal, Data Engineering

Mastercard · Arlington, Virginia

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

Senior Principal, Data Engineering

Overview:
Mastercard Services Technology is seeking a Senior Principal Data Engineer to help drive our mission of unlocking the full potential of our data assets through innovation, automation, and engineering excellence. This is a highly technical, hands-on individual contributor role focused on building and evolving modern data platforms that enable secure, scalable, and governed access to data across both cloud and on-premises environments.
As a senior technical leader, you will be responsible for designing, building, and optimizing enterprise-scale data platforms across AWS and Azure. You will define architectural standards, champion engineering best practices, and lead the implementation of cloud-native data solutions that support Mastercard's growing data ecosystem. While this role requires strong technical leadership and the ability to influence across teams, it does not include direct people management responsibilities.
The ideal candidate is a builder at heart, someone who enjoys writing code, solving complex engineering challenges, driving platform modernization initiatives, and partnering with globally distributed engineering teams to deliver measurable business impact. If you thrive in a fast-paced environment and are passionate about creating scalable, secure, and future-ready data platforms, this role is for you.

Role:
• Design and architect end-to-end cloud-native data platform solutions, including modern lakehouse architectures leveraging AWS (S3) and Azure (Data Lake) with Databricks and related ecosystem tools.
• Lead by doing through hands-on development of DevOps capabilities, including CI/CD pipelines, Infrastructure-as-Code, and automated environment provisioning across multi-cloud platforms.
• Define and enforce cloud security architecture standards, including IAM design, encryption strategies, network security, and regulatory compliance (e.g., GDPR, HIPAA).
• Establish enterprise-grade data governance frameworks covering data cataloging, lineage, classification, and access control using tools such as AWS Lake Formation and Azure Purview.
• Architect and deliver scalable data engineering solutions, including ETL/ELT pipelines, data lakes, and data warehouse systems supporting analytics and reporting use cases.
• Implement and evolve Medallion Lakehouse architectures (Bronze, Silver, Gold) leveraging AWS services (Glue, Lake Formation) and analytics engines such as Databricks, EMR, and Athena.
• Translate complex business requirements into scalable, secure, and maintainable technical solutions in partnership with product, engineering, and analytics stakeholders.
• Provide hands-on technical leadership by mentoring engineers and DevOps practitioners, promoting engineering excellence, ownership, and continuous improvement.
• Drive operational excellence through proactive monitoring, troubleshooting, and optimization of data platforms for performance, scalability, reliability, and cost efficiency.
• Define and document architectural standards, design patterns, and operational best practices to enable consistency and scalability across teams.
• Evaluate emerging technologies and industry trends in cloud, data, and DevOps to ensure the platform remains modern, efficient, and future-ready.
• Actively participate in architecture reviews, technical design discussions, Agile ceremonies, and iterative planning and estimation sessions while influencing cross-team technical direction.

All About You:
• Deep expertise designing, building, and operating enterprise-scale cloud and data platforms.
• Hands-on experience with AWS services including S3, EC2, Lambda, Glue, Redshift, EMR, Athena, and Lake Formation.
• Hands-on experience with Azure services including Data Factory, Synapse, Fabric, Azure Data Lake, and related technologies.
• Strong software engineering background with experience building production-grade cloud-native solutions.
• Expertise implementing Infrastructure-as-Code and CI/CD pipelines using Terraform, CloudFormation, Bicep/ARM, Azure DevOps, GitLab CI/CD, or similar tools.
• Strong understanding of cloud security architecture, IAM, encryption, governance, and compliance frameworks.
• Extensive experience with Spark, PySpark, distributed data processing, and large-scale data engineering systems.
• Proficiency in Python and scripting languages such as Bash or PowerShell.
• Demonstrated success delivering production-scale Medallion Lakehouse architectures.
• Experience with containerization and orchestration technologies including Docker, Kubernetes, ECS, and AKS.
• Strong knowledge of observability, monitoring, and logging platforms such as CloudWatch, Azure Monitor, ELK, or Grafana.
• Experience implementing cloud cost optimization and FinOps best practices.
• Proven ability to influence technical direction, drive consensus, and deliver outcomes across cross-functional teams without direct authority.
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

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 the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: 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; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.

Pay Ranges

Arlington, Virginia: $244,000 - $390,000 USD

O'Fallon, Missouri: $212,000 - $339,000 USD

Data & ML pay context

Based on 1,582 disclosed Data & ML salaries on RoleSuite, the role pays a median of $162K/year, with most offers between $127K and $204K (10th–90th percentile: $105K–$246K).

This posting lists $244K–$390K, above the $162K market median.

See the full Data & ML salary breakdown →
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