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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Software Engineer, Data Architecture - **Company:** Mastercard - **Location:** Arlington, VA, United States - **Salary:** $170,000.0 - $337,000.0 - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Batch Processing, Cyber Security, Data Architecture, Data Governance, Data Systems, Distributed Data Store, Data Streaming, Google Cloud, System Availability, Snowflake, Apache Spark, HybridCloud, Data Lakes, Information Technology, Low Latency, Apache Flink, Data Analytics, Apache Kafka, Apache Nifi, Data Management, Databricks - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=954c4cfca628bb08 ## About the Role * Proven experience operating as a Principal Engineer or equivalent, leading enterprise scale data architecture or platform strategy. * Deep expertise designing, building, and operating distributed data systems at global scale. * Hands on experience with technologies such as Apache Spark, Kafka, Flink, and NiFi. * 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 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. ## Description Mastercard's Data & Analytics organization is seeking a visionary Principal Software Engineer, Data Architecture to shape and evolve our global enterprise data architecture. Reporting to the SVP, this role serves as the senior technical authority defining how data is designed, governed, secured, and distributed across Mastercard's complex, global ecosystem. You will set the architectural vision for modernizing data platforms across a hybrid cloud and on premises environment, supporting both high throughput batch processing and low latency, real time use cases. Your leadership will enable Mastercard's "edge everywhere, run anywhere" strategy, allowing products and platforms to deploy data workloads consistently, securely, and at scale across our worldwide footprint. This role combines deep hands on technical expertise with enterprise influence, enabling Mastercard to unlock the full value of its data while meeting stringent regulatory, resiliency, and performance requirements. Role: * Serve as the foundational technical leader for enterprise data architecture, partnering closely with the SVP and senior technology leadership. * Act as a trusted advisor to C suite and executive stakeholders, translating business strategy into scalable data architecture decisions. * Define and evolve the global data architecture roadmap across hybrid (cloud + on prem) 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, treating data as a product with federated ownership, governance, and self service enablement. * Establish organization wide architecture standards and development 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. * Mentor and influence global engineering teams, fostering a culture of technical excellence, accountability, and thoughtful risk taking., 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Enabling intelligent logistics automation: home-grown Industrial IoT platform at Austrian Post](https://www.wearedevelopers.com/videos/2018-enabling-intelligent-logistics-automation-home-grown-industrial-iot-platform-at-austrian-post) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [The 12 Best Jobs for Software Engineers](https://www.wearedevelopers.com/magazine/401-the-12-best-jobs-for-software-engineers)