Manager - Data Platform Engineering

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

Manager - Data Platform Engineering

Overview:
Mastercard is seeking a Manager, Data Platform Engineering to lead and oversee the operations, enhancements, and scaling of our enterprise-wide Data Platform. This platform currently includes core components such as Apache NiFi, Apache Spark, and MinIO, and supports multiple internal applications for data ingestion, processing, and storage.
We are looking for an experienced manager who can drive technical excellence and lead a team focused on ensuring platform reliability, performance, and scalability. As we evolve our platform, you will also manage the integration and adoption of new technologies such as Kubernetes and Apache Airflow, enabling high availability, streamlined workflows, and continuous improvement across our data ecosystem.
This is a hybrid position based in O’Fallon, MO, requiring three days per week onsite.

Role:
• Lead and manage a team responsible for maintaining, optimizing, and upgrading core data platform components including Apache NiFi, Apache Spark, and MinIO.
• Drive the adoption and integration of emerging technologies, such as Kubernetes for orchestration and Apache Airflow for workflow management.
• Partner with DevOps teams to manage CI/CD pipelines and containerized environments, ensuring seamless deployment and scalability.
• Collaborate closely with cross-functional teams (Data Science, Analytics, and Application Development) to understand requirements and deliver efficient data ingestion and processing workflows.
• Establish and enforce best practices, automation standards, and monitoring frameworks to ensure the platform’s reliability, scalability, and security.
• Oversee incident management, including response coordination, root cause analysis, and continuous improvement initiatives.
• Plan and execute platform upgrades, migrations, and capacity planning to support future growth.
• Facilitate collaboration between engineering teams to deliver cohesive enhancements and minimize disruption to business-critical applications.
• Define, monitor, and report on key performance indicators (KPIs) to measure platform health, performance, and team effectiveness.
• Mentor and develop team members, fostering a culture of innovation, accountability, and continuous learning.

All About You:
• Hands-on experience in data engineering, data platform management, or a related technical domain.
• Proven experience leading data engineering or platform engineering teams.
• Hands-on expertise with modern data architectures and cloud-based solutions (AWS preferred)
• Background in Java for data processing and automation is desired.
• Proven experience managing large-scale data platforms with components like Apache NiFi, Apache Spark, and object storage solutions (MinIO or equivalent).
• Strong working knowledge of Kubernetes and container orchestration in production environments.
• Familiarity with workflow orchestration tools, preferably Apache Airflow.
• Skilled in Linux/Unix administration, scripting, and automation for large-scale systems.
• Deep understanding of data ingestion, ETL/ELT pipelines, and distributed data processing.
• Experience implementing monitoring, alerting, and incident management solutions in production environments.
• Excellent communication skills, with the ability to tailor technical concepts to executive, operational, and technical audiences.
• Strong interpersonal and collaboration skills, with the ability to foster a data-driven and innovation-focused culture.
• Bachelor’s degree in Data Science, Computer Science, Information Technology, Business Administration, or a related field. Equivalent experience will also be considered.

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.

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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 t