Principal Software Engineer, Data Architecture

Mastercard Mastercard · Fintech · O Fallon, MO +3 · Engineering

Mastercard is seeking a Principal Software Engineer, Data Architecture to define and evolve their global enterprise data architecture. This role involves setting the architectural vision for modernizing data platforms across hybrid cloud and on-premises environments, supporting both batch and real-time use cases. The engineer will act as a senior technical authority, ensuring data is designed, governed, secured, and distributed securely and at scale, while meeting stringent regulatory and performance requirements. The role emphasizes championing Data Mesh principles, establishing architecture standards, and leading the adoption of modern data technologies.

What you'd actually do

  1. Serve as the foundational technical leader for enterprise data architecture, partnering closely with the SVP and senior technology leadership.
  2. Define and evolve the global data architecture roadmap across hybrid (cloud + on prem) environments.
  3. Architect secure, resilient solutions that meet global regulatory and compliance mandates, including GDPR, ISO 20022, and regional data localization requirements.
  4. Champion Data Mesh principles, treating data as a product with federated ownership, governance, and self service enablement.
  5. Lead the modernization of legacy data platforms to cloud native architectures across AWS, Azure, and GCP.

Skills

Required

  • enterprise scale data architecture or platform strategy
  • designing, building, and operating distributed data systems at global scale
  • cloud native architectures across AWS, Azure, and/or GCP
  • integrating AI driven capabilities into data platforms, with appropriate governance and guardrails for emerging use cases, including agentic commerce
  • data governance, security, and regulatory compliance in highly regulated, global environments
  • lead and influence architectural initiatives within Agile, SAFe, or product centric delivery models
  • influence technical and business decisions at all levels, including C-suite stakeholders
  • executive presence
  • translate complex architecture concepts into business language
  • exceptional communication skills
  • articulate complex technical concepts to executive and non technical audiences

Nice to have

  • Apache Spark
  • Kafka
  • Flink
  • NiFi
  • Databricks
  • Snowflake
  • Delta Lake
  • streaming platforms

What the JD emphasized

  • global enterprise data architecture
  • hybrid cloud and on premises environment
  • low latency, real time use cases
  • edge everywhere, run anywhere
  • stringent regulatory, resiliency, and performance requirements
  • global regulatory and compliance mandates
  • GDPR
  • ISO 20022
  • regional data localization requirements
  • Data Mesh principles
  • federated ownership
  • governance
  • self service enablement
  • organization wide architecture standards
  • development best practices
  • modernization of legacy data platforms
  • cloud native architectures
  • AWS
  • Azure
  • GCP
  • modern data technologies
  • Databricks
  • Snowflake
  • Delta Lake
  • streaming platforms
  • real time and batch analytics use cases
  • high availability
  • mission critical workloads
  • global engineering teams
  • technical excellence
  • accountability
  • thoughtful risk taking
  • enterprise scale data architecture or platform strategy
  • distributed data systems at global scale
  • Apache Spark
  • Kafka
  • Flink
  • NiFi
  • cloud native architectures
  • AWS
  • Azure
  • GCP
  • AI driven capabilities into data platforms
  • governance
  • guardrails
  • emerging use cases
  • agentic commerce
  • data governance
  • security
  • regulatory compliance
  • highly regulated, global environments
  • lead and influence architectural initiatives
  • Agile
  • SAFe
  • product centric delivery models
  • product
  • engineering
  • business stakeholders
  • influence technical and business decisions
  • C-suite stakeholders
  • executive presence
  • complex architecture concepts
  • business language
  • exceptional communication skills
  • complex technical concepts
  • executive and non technical audiences
  • Strong Decency Quotient (DQ)
  • inclusive
  • collaborative
  • high performing teams
  • Computer Science
  • Engineering
  • Data Science
  • quantitative field
  • equivalent practical experience
  • work authorization sponsorship
  • eligible to work in the United States
  • employer sponsorship
  • Mastercard’s security policies and practices
  • confidentiality and integrity of the information
  • suspected information security violation or breach
  • periodic mandatory security trainings