Principal Software Engineer, Data Architecture

Overview: Mastercard's Data & Analytics organization is seeking a visionary Principal Software Engineer, Data Architecture to define and advance our global enterprise data architecture strategy. Reporting to the Vice President of Data Engineering, this role serves as the senior technical authority for how data is architected, governed, secured, and enabled across Mastercard's complex global ecosystem.

The successful candidate will establish the architectural vision for modernizing data platforms across hybrid cloud and on-premises environments, supporting both high-volume batch processing and low-latency, real-time workloads. This leader will play a critical role in enabling Mastercard's "Edge Everywhere, Run Anywhere" strategy, ensuring data platforms can be deployed consistently, securely, and at scale across diverse geographies and regulatory environments.

This position combines deep hands-on technical expertise with enterprise influence, driving architectural decisions that maximize the value of Mastercard's data assets while meeting the highest standards for security, resiliency, compliance, and operational excellence.

Role: - Serve as the senior technical leader for enterprise data architecture, partnering closely with the VP and senior technology leadership. - Act as a trusted advisor to executive stakeholders, translating business strategy into scalable, secure, and resilient data architecture decisions. - Define and evolve Mastercard's global data architecture strategy across hybrid cloud and on-premises environments. - Architect secure, resilient solutions that meet global regulatory and compliance mandates, including GDPR, ISO 20022, and regional data localization requirements. - Champion Data Mesh principles, enabling data-as-a-product capabilities, federated ownership, governance, and self-service access. - Establish and drive enterprise architecture standards, design patterns, and engineering best practices through the Data & Analytics Architecture Review Board. - Lead the modernization of legacy data platforms to cloud native architectures across AWS, Azure, and GCP. - Drive adoption of modern data technologies, including Databricks, Snowflake, Delta Lake, and streaming platforms. - Enable both real time and batch analytics use cases to support high availability, mission critical workloads. - Evaluate and incorporate emerging technologies, including AI-enabled data platforms and agent-based architectures. - Mentor and influence global engineering teams, fostering a culture of technical excellence, accountability, and thoughtful risk taking.

All About You: - Proven experience as a Principal Engineer, Lead Architect, or equivalent technical leadership role driving enterprise-scale data architecture and platform strategy. - Deep expertise designing, building, and operating distributed data systems at global scale. - Strong hands-on experience with technologies such as Apache Spark, Kafka, Flink, NiFi, Databricks, Snowflake, and modern cloud-native data platforms. - Demonstrated success modernizing data platforms using cloud native architectures across AWS, Azure, and/or GCP. - Experience integrating AI driven capabilities into data platforms, with appropriate governance and guardrails for emerging use cases, including agentic commerce. - Strong understanding of data governance, security, and regulatory compliance in highly regulated, global environments. - Proven ability to lead and influence architectural initiatives within Agile, SAFe, or product centric delivery models, partnering effectively with product, engineering, and business stakeholders. - Demonstrated ability to influence technical and business decisions at all levels, including C-suite stakeholders. - Strong executive presence with the ability to translate complex architecture concepts into business language. - Exceptional communication skills, with the ability to articulate complex technical concepts to executive and non-technical audiences. - Strong Decency Quotient (DQ) with a track record of building inclusive, collaborative, high performing teams. - Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience.

This role is not eligible for Mastercard's work authorization sponsorship. As such, candidates must be eligible to work in the United States, now as well as in the future, without employer sponsorship.