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Vice President, Data Platform Engineering

Job in Arlington, Arlington County, Virginia, 22201, USA
Listing for: MasterCard
Full Time position
Listed on 2026-01-01
Job specializations:
  • IT/Tech
    Data Engineer, Data Science Manager
Job Description & How to Apply Below
Vice President, Data Platform Engineering page is loaded## Vice President, Data Platform Engineering locations:
Arlington, Virginia:
O'Fallon, Missouri time type:
Full time posted on:
Posted Yesterday job requisition :
R-264553
** 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**### Vice President, Data Platform Engineering### 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., Lang Chain, CrewAI, Auto Gen) 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…
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