Vice President, Data Engineering

Mastercard Inc.; Hyderabad; Hybrid; INR 24,108,000 - 33,751,000; Full time

Job summary

Mastercard Inc. seeks a Vice President, Data Platform Engineering to lead enterprise data infrastructure modernization, global team leadership, and AI-driven automation.

The role focuses on building a scalable, secure data platform that ingests, processes, and delivers data across business units, leveraging Spark, NiFi, Airflow, and advanced AI agents. Hybrid, based in US with three onsite days.

Qualifications

• Hands-on data engineering and platform strategy experience.
• Proven leadership of global data/platform teams.
• Experience modernizing distributed data platforms (Spark, Kafka, NiFi).
• Strong Python and SQL skills; familiarity with cloud data services.
• Experience AI-augmented or agent-driven systems is a plus.

Responsibilities

• Drive modernization from legacy on-prem to cloud-native platforms.
• Design and lead a Multi-Agent ETL Platform with AI agents.
• Define pipelines with Airflow, NiFi, dbt, Spark, Kafka or Dagster.
• Ensure data governance, cataloging, versioning, lineage.
• Collaborate with Data Science, Analytics, App Dev teams.

Skills

Data engineering

Leadership

Python

SQL

Cloud platforms

Data governance

AI agents

Education

Bachelor's degree in CS/DS

Tools

Apache Spark

Kafka

Nifi

dbt

Airflow

Dagster

Hadoop

Job description

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 are 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.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we are 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 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.

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 Mastercards 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.

Everyone wants easier ways to pay; we invent them. Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. Retailers want to fight fraud; we provide the tools.