Director, 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._

• Title and Summary

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Director, Data Engineering Overview:

We are looking for a Director, Data Engineering to lead the strategy, design, and operation of our enterprise-scale data platform that powers analytics, applications, and AI-enabled use cases across the organization. This role is firmly grounded in data engineering and platform engineering—owning platform vision, architecture, and execution across ingestion, processing, orchestration, storage, reliability, and scalability for batch and streaming workloads. The Director will ensure the platform enables advanced capabilities, including AI, while meeting enterprise standards for security, governance, and operational excellence. The focus is on building and evolving robust data infrastructure that makes data and AI capabilities easy, safe, and scalable for downstream teams to consume, while positioning the platform for cloud modernization and long-term growth. Strong technical credibility is expected, and the leader needs to be comfortable with hands on technology work.

Role:

• Data Platform Engineering  Own the end-to-end vision, roadmap, and architecture for the enterprise data platform.

 Provide technical and organizational leadership over scalable data pipelines using technologies such as Apache NiFi, Airflow, Spark (batch / streaming), and synonymous technologies across On-Prem and Cloud platforms.  Ensure consistent design and governance of data ingestion, transformation, enrichment, and access patterns across teams.  Define and govern data schemas, contracts, and transformations, ensuring data quality, consistency, and backward compatibility.  Drive platform performance, scalability, reliability, and cost optimization across environments.  Establish platform-wide data quality standards, monitoring, alerting, and SLAs for critical data assets.  Oversee use of object storage platforms (MinIO / Ceph / S3-compatible APIs) including data layout, lifecycle management, and retention policies.  Own operational readiness for batch and near-real-time processing, including incident management and root cause analysis.

• Platform & Infrastructure Integration  Provide architectural oversight for containerized data workloads and services deployed on Kubernetes-based platforms.

 Partner closely with DevOps, SRE, and Infrastructure teams to ensure observability, resiliency, and operational maturity.  Guide CI/CD, automation, and infrastructure-as-code practices for data platform components.  Lead platform modernization efforts, capacity planning, and preparation for hybrid or public cloud adoption.

• AI Enablement  Partner with AI/ML teams to ensure the data platform effectively supports AI-driven use cases (e.

g., enrichment, search, anomaly detection).  Define patterns for integrating AI-enabled capabilities (e.g., PII detection, classification, summarization) into enterprise data workflows.  Ensure AI-enabled data pipelines comply with enterprise security, privacy, and governance requirements.  Enable scalable, repeatable data foundations that allow AI teams to operate efficiently without direct platform customization.

• Collaboration & Enablement  Act as a senior partner to application teams, analytics teams, AI teams, and product leaders to translate business needs into platform capabilities.

 Communicate platform strategy, risks, and trade-offs clearly to executive and senior stakeholder audiences.  Establish documentation, standards, and best practices to support self-service and platform adoption.  Build, mentor, and lead senior engineering managers and technical leaders, raising the overall engineering bar.

All About You:

• Proven hands-on experience in data engineering, platform engineering, or distributed systems.
• Previous experience leading enterprise-scale data engineering teams.
• Proven track record owning and operating mission-critical data platforms in production environments.
• Strong architectural understanding of enterprise data platforms and distributed data systems.
• Hands-on background (current or prior) with:  Apache Spark (batch; streaming preferred)  Apache NiFi or comparable ingestion frameworks  Apache Airflow or similar orchestration tools
• Experience with object storage systems (S3-compatible storage).
• Experience operating data workloads on Kubernetes-based platforms.
• Strong understanding of data modeling, schema evolution, pipeline design, and reliability patterns.
• Exposure to public cloud platforms (AWS, Azure, or GCP) and hybrid deployment models.
• Ability to apply cloud-native design principles to guide platform modernization and migration strategies.
• Strong ownership mindset and accountability for enterprise platforms.
• Excellent executive communication and stakeholder management skills.
• Pragmatic decision-making in complex, ambiguous environments.
• Proven ability to build, mentor, and retain high-performing engineering leaders.
• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field.

Equivalent practical experience may also be considered.

Nice-to-Have :

• Experience with Kafka or event-driven architectures.
• Familiarity with Lakehouse technologies (Parquet, Delta Lake, Iceberg, or Hudi).
• Experience enabling AI/ML use cases through data platforms (not model development).
• Exposure to monitoring and observability stacks (e.g., Prometheus, Grafana, ELK).
• Background in regulated or security-conscious environments (e.

g., financial services). Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

• 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.

In line with Mastercard's total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.

• Pay Ranges

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Purchase, New York:

$195,000 - $323,000

USD Boston, Massachusetts:

$196,000 - $323,000 USD