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 EngineerOverviewWe are seeking a Lead Data Engineer with expertise in Apache Spark, Apache Iceberg, Apache Airflow, and AWS to design and build the next generation of our finance data platform. You will own finance-focused data products while contributing to foundational platform capabilities and engineering standards that scale across the enterprise.
The ideal candidate is a hands-on engineer who thrives in modern Lakehouse architecture, large-scale pipeline development and analytical mindset.
Key Responsibilities
Data Products
• Design, develop, and maintain data products
• Ensure data products meet quality, auditability, lineage, and compliance standards
Platform Engineering & Framework Development
• Build reusable data engineering frameworks and accelerators used across multiple teams
• Develop standardized patterns for ingestion, transformation, orchestration, monitoring, and data quality
• Establish and enforce best practices for Spark, Iceberg, Airflow, and cloud-native engineering
• Drive adoption of self-service platform capabilities and common engineering standards
• Build and optimize Apache Iceberg-based lakehouse solutions for analytical and operational workloads
Cloud Engineering
• Build cloud-native solutions on AWS - S3, EMR, Glue, Lambda, ECS/EKS, CloudWatch
• Implement CI/CD pipelines, automated testing, and Infrastructure-as-Code
All About You
• 8+ years of experience in data engineering, data platform development, or related technical roles.
• Leading design and implementation of scalable enterprise data solutions and reusable engineering frameworks
• Knowledge of data mesh or data product architectures in enterprise settings.
• Advanced hands-on experience with Apache Spark (PySpark) and distributed data processing at enterprise scale.
• Deep hands-on experience with Apache Iceberg or similar open table formats
• Solid understanding of CI/CD pipelines, infrastructure-as-code and DevOps practices.
• Experience with data governance, data quality frameworks, and metadata management tools.
• Strong experience with AWS Cloud services, including services such as Amazon S3, EMR, Glue, Lambda, ECS/EKS, and CloudWatch for developing, deploying, and managing cloud-native data solutions.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 reasonable_accommodation@mastercard.com 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.
Pay Ranges
Miami, Florida: $140,000 - $231,000 USD