# Vice President, Data Engineering at Mastercard

AI Level 3, AI centrality 70 out of 100. Hyderabad, India.

## Details

- Company: [Mastercard](https://jobsbylevel.com/companies/mastercard)
- AI level: AI Level 3 (score 70 out of 100)
- Location: Hyderabad, India
- Posted: October 7, 2026
- Apply: https://jobsbylevel.com/go/5984491c-0f48-4f80-9ef8-e7bad42d7789

## Description

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 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. Vice President, Data Platform Engineering Overview: Mastercard is seeking a Vice President, Data Platform Engineering team, who will be responsible for strategic leadership, operational oversight, and innovation for 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. The 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 seeking an experienced and visionary Vice President 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 uses AI agents, orchestration frameworks, and modern data engineering tools to extract, transform, and load data from legacy diverse systems. The ideal candidate combines data engineering expertise, AI/automation experience, and leadership skills to drive innovation and efficiency in our 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

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