Job Title:

Vice President, Data Platform Engineering

Overview:

Overview:
Mastercard is seeking a Vice President, Data Platform Engineering, responsible for providing strategic leadership, operational oversight, and driving innovation across our enterprise-wide Data Platform. Mastercard's Data & Analytics organization is undergoing a bold transformation to modernize our global data ecosystem-unlocking value through secure, scalable, and compliant data capabilities.
Our current platform includes core components such as Apache NiFi, Apache Spark, and MinIO, supporting multiple internal applications for data ingestion, processing, and storage. We are now seeking an experienced and visionary leader to build and lead a Multi-Agent ETL Platform team. This role will design, develop, and operationalize an intelligent, scalable, and automated data pipeline ecosystem that leverages AI agents, orchestration frameworks, and modern data engineering tools to extract, transform, and load data from diverse legacy systems.
The ideal candidate will bring deep data engineering expertise, AI-driven automation experience, and proven leadership skills to advance innovation, scalability, and efficiency across Mastercard's data infrastructure.
This is a hybrid position based in O'Fallon, MO or Arlington, VA, requiring three days per week onsite.

Role:
• Drive modernization from legacy and on-prem systems to modern, cloud-native, and hybrid data platforms.
• Architect and lead the development of a Multi-Agent ETL Platform for batch and event streaming, integrating AI agents to autonomously manage ETL tasks such as data discovery, schema mapping, and error resolution.
• Define and implement data ingestion, transformation, and delivery pipelines using scalable frameworks (e.g., Apache Airflow, Nifi, dbt, Spark, Kafka, or Dagster).
• Leverage LLMs, and agent frameworks (e.g., LangChain, CrewAI, AutoGen) to automate pipeline management and monitoring.
• Ensure robust data governance, cataloging, versioning, and lineage tracking across the ETL platform.
• Define project roadmaps, KPIs, and performance metrics for platform efficiency and data reliability.
• Establish and enforce best practices in data quality, CI/CD for data pipelines, and observability.
• 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.
• Build relationships and communicate effectively with internal and external stakeholders, including senior executives, to influence data-driven strategies and decisions.
• Continuously engage and improve teams' performance by conducting recurring meetings, knowing your people, managing career development, and understanding who is at risk.
• Oversee deployment, monitoring, and scaling of ETL and agent workloads across multi cloud environments.
• Continuously improve platform performance, cost efficiency, and automation maturity.

All About You:
• Hands-on experience in data engineering, data platform strategy, or a related technical domain.
• Proven experience leading global data engineering or platform engineering teams.
• Proven experience in building and modernizing distributed data platforms using technologies such as Apache Spark, Kafka, Flink, NiFi, and Cloudera/Hadoop.
• Strong experience with one or more of data pipeline tools (Nifi, Airflow, dbt, Spark, Kafka, Dagster, etc.) and distributed data processing at scale.
• Experience building and managing AI-augmented or agent-driven systems will be a plus.
• Proficiency in Python, SQL, and data ecosystems (Oracle, AWS Glue, Azure Data Factory, BigQuery, Snowflake, etc.).
• Deep understanding of data modeling, metadata management, and data governance principles.
• Proven success in leading technical teams and managing complex, cross-functional projects.
• Passion for staying current in a fast-paced field with proven ability to lead innovation in a scaled organization.
• Excellent communication skills, with the ability to tailor technical concepts to executive, operational, and technical audiences.
• Expertise and ability to lead technical decision-making considering scalability, cost efficiency, stakeholder priorities, and time to market.
• Proven track leading high-performing teams with experience leading and coaching director level reports and experienced individual contributors.
• 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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