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

Senior Vice President, Data Engineering

Job Description Summary:

Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and elevating the digital payments experience. We deliver value-added services and leverage data-driven insights to power performance.

Reporting to the Executive Vice President of Data & Analytics, the Senior Vice President (SVP), Data Engineering will lead the global strategy, architecture, and execution of our data collection and enrichment capabilities – particularly in the card domain. This leader will play a pivotal role in transitioning from legacy systems to modern, cloud-native data platforms that fuel decision-making, drive innovation, and enable real-time business intelligence at scale.

Key Responsibilities:

Strategic Leadership & Business Alignment:

Define and execute the vision and roadmap for enterprise data engineering, aligned with the company’s digital transformation goals.

Establish a “Data-as-a-Product” approach, delivering domain-specific, reusable, and business-ready data products across the organization.

Partner with AI/ML and advanced analytics teams to ensure that data platforms are optimized for experimentation, training, and real-time inference.

Own the enterprise data architecture, ensuring alignment across engineering, analytics, governance, and infrastructure functions.

Partner closely with stakeholders across Product, Tech, Cybersecurity, Fraud, Risk, and Regional teams to ensure cross-functional success.

Enable external-facing platforms and partner ecosystems by building secure, high-performance data APIs and clean rooms for data sharing.

Evangelize data engineering best practices and promote alignment across lines of business.

Technical Execution

Oversee robust, scalable ETL/ELT pipelines for ingesting and enriching switched card data in both batch and streaming formats.

Lead initiatives for:

Merchant Data Matching & Aggregation using graph databases and third-party enrichment.

Data Localization & Residency in line with in-country regulations.

Data Quality Monitoring & Observability across all pipeline stages using automated auditing, profiling, and lineage tools.

Enable real-time data delivery and feature engineering for ML and analytics teams using platforms like Delta Lake, Flink, and Kafka.

Drive modernization and migration of legacy systems to cloud-native architectures, using a phased, business-safe strategy.

Cloud & Platform Engineering:

Lead adoption and optimization of cloud-native platforms including:

AWS (e.g., S3, Glue, EMR, Redshift, Kinesis)

Azure (e.g., ADLS, Synapse, Data Factory)

GCP (e.g., Big Query, Dataflow)

Implement best practices for data lake and lakehouse architectures, supporting structured and unstructured data at petabyte scale.

Use Infrastructure-as-Code (IaC) tools like Terraform and CI/CD tools (e.g., Jenkins, GitHub Actions) to deploy secure, scalable pipelines.

Security, Compliance & Governance

Collaborate with Information Security and Compliance teams to ensure that all data engineering practices comply with PCI-DSS, GDPR, CCPA, SOC 2, and other applicable frameworks.

Implement privacy-by-design principles, including encryption, role-based access control, and sensitive data masking at rest and in transit.

Ensure consistent data governance, metadata management, and lineage tracking through tools such as Collibra, Alation, or Apache Atlas.

Team Leadership & Organizational Influence:

Lead, mentor, and scale a high-performing global engineering team across multiple geographies and time zones.

Develop and implement talent development, leadership pipeline, and succession planning frameworks.

Own and manage multi-million-dollar program budgets and deliver against financial, efficiency, and growth KPIs.

Define and monitor success metrics including:

Data pipeline uptime and SLA/SLO compliance

Data freshness and latency

Pipeline failure rate and recovery time

Developer productivity and velocity

Cloud cost optimization and usage efficiency

Cultivate a culture of innovation, excellence, operational ownership, and accountability.

Qualifications & Experience:

Technical Skills:

15+ years of progressive experience in data engineering, including 7+ years in executive or senior leadership roles.

Proven experience building distributed batch and streaming data pipelines in cloud environments using Spark, Kafka, Flink, and Airflow.

Deep knowledge of data lakes, lakehouses, object storage, and hybrid architectures.

Fluency in SQL, Python, Java, or Scala for data transformation and pipeline automation.

Hands-on experience with cloud-native big data platforms (AWS, Azure, GCP) and tools like Databricks, Snowflake, or Redshift.

Expertise in data quality, observability, governance, and compliance frameworks.

Leadership & Industry Experience:

Deep understanding of the Payments and/or Fintech industry, including merchant ecosystems, card data flows, and fraud/risk contexts.

Proven experience working with high-cardinality, high-volume data sources with strict latency and accuracy requirements.

Demonstrated success managing large global engineering teams (100+), including distributed agile squads.

Track record of organizational change management and leading large-scale platform migrations.

Exceptional executive communication skills with a proven ability to influence C-level stakeholders across a matrixed, global organization and across technology, product, and executive teams globally.

Strong business acumen and ability to manage budgets, prioritize investments, and deliver on growth and cost-efficiency targets.

Why Join Us:

This role is a unique opportunity to shape the core data platform that underpins the global payments ecosystem. As SVP of Data Engineering, you'll lead critical modernization efforts, enable machine learning and advanced analytics, and drive enterprise-wide data excellence. Your
#AI3

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.