MastercardVice President, Data Engineering
Mastercard is hiring a Vice President, Data Engineering in Hyderabad, India. Level rates it ; you can apply on Level.
AI in this role
Lead enterprise data platform engineering and build an AI-driven multi-agent ETL pipeline ecosystem for cloud modernization.
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 EngineeringOur PurposeMastercard 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.
How we rate this
Vice President, Data Engineering at Mastercard rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where etl was part of your work. What did you do?
- Tell me about a project where multi agent systems was part of your work. What did you do?
- Tell me about a project where cloud native was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Data Engineering, ETL, Multi Agent Systems, and Cloud Native. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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