Vice President, Data Engineering

Mastercard; Hyderabad; Hybrid; INR 24,225,000 - 33,915,000; Full time

Job summary

Mastercard is seeking a Vice President to lead Data Platform Engineering, driving modernization from legacy systems to cloud-native, scalable platforms. You will architect a Multi-Agent ETL Platform, integrate AI agents for autonomous data tasks, and define pipelines with Airflow, NiFi, dbt, Spark, Kafka, and Dagster.

You will partner with Data Science, Analytics, and Application Development to ensure governance, reliability, and cost efficiency while mentoring senior engineers and aligning with

Qualifications

• Hands-on experience in data engineering, data platform strategy, or a related technical domain.
• Proven experience leading global data engineering or platform engineering teams.
• Experience 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.

Responsibilities

• 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.

Skills

Data engineering

Data platform strategy

Leadership

Distributed data platforms

Spark

Kafka

Flink

NiFi

Airflow

dbt

Dagster

Python

SQL

Data governance

Education

Bachelor’s degree in Data Science, Computer Science, Information Technology, Business Administration, or related field

Tools

Apache NiFi

Apache Spark

Kafka

Flink

MinIO

Airflow

dbt

Dagster

LangChain

Job 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 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 Mastercard’s 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.