Software Engineer, Data

# Principal Software Engineer, Data Architecture

## About the Role

Mastercard’s Data & Analytics organization is seeking a visionary **Principal Software Engineer, Data Architecture** to define and advance the company’s global enterprise data architecture strategy. Reporting to the Vice President of Data Engineering, this senior technical leadership role will shape strategic platforms for secure external data exchange and make enterprise data easier for product teams, consultants, and analysts to discover, access, and use.

You’ll combine deep hands-on technical expertise with enterprise-level influence to transform complex, fragmented data processes into scalable, self-service experiences. The successful candidate will establish architectural vision, drive technology strategy, and maximize the value of Mastercard’s data assets while maintaining high standards for security, resiliency, regulatory compliance, and operational excellence.

## Key Responsibilities is a merit-based, inclusive, equal opportunity employer and considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disability or

• - Serve as the senior technical leader for enterprise data architecture, partnering closely with the VP and senior technology leadership.
• - Advise executive stakeholders and translate business strategy into scalable, secure, and resilient data architecture decisions.
• - Define the technical vision and architecture for enterprise data onboarding, data exchange, data discovery, and data consumption capabilities.
• - Develop technology and platform roadmaps that balance immediate business needs with long-term scalability and reuse.
• - Establish and drive enterprise architecture standards, design patterns, and engineering best practices through the Data & Analytics Architecture Review Board.
• - Drive adoption of modern data technologies, including Databricks, Snowflake, Delta Lake, and streaming platforms.
• - Evaluate and incorporate emerging technologies, including AI-enabled data platforms and agent-based architectures.
• - Integrate AI-driven capabilities into data platforms with appropriate governance and guardrails for emerging use cases, including agentic commerce.
• - Mentor and influence global engineering teams while fostering technical excellence, accountability, inclusivity, collaboration, and thoughtful risk-taking.
• - Influence technical and business decisions across organizational levels, including C-suite stakeholders.

## Required Qualifications

• - Proven experience as a **Principal Engineer, Lead Architect, Lead Engineer**, or equivalent technical leadership role driving enterprise-scale data architecture and platform strategy.
• - Extensive experience architecting and building large-scale **data platforms, distributed systems, and enterprise integration solutions** across on-premises and cloud environments.
• - Experience with technologies such as **Spark, Kafka, Flink, NiFi, Hadoop/Cloudera, Databricks**, and modern cloud-native data services.
• - Experience integrating **AI-driven capabilities into data platforms**, including appropriate governance and guardrails for emerging use cases.
• - Experience building reusable platforms serving multiple products, teams, or business domains.
• - 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**.
• - Ability to partner 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 and ability to translate complex architecture concepts into business language.
• - Exceptional communication skills, including the ability to explain complex technical concepts to executive and non-technical audiences.
• - Strong Decency Quotient (DQ) and 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**.
• - Must be eligible to work in the United States now and in the future **without employer sponsorship**.

## Preferred Qualifications

- The source job description does not identify additional qualifications as preferred, nice-to-have, or optional.

## Skills & Competencies

• - **Enterprise data architecture:** Data architecture strategy, platform architecture, enterprise integration, and architectural standards.
• - **Data engineering:** Large-scale data platforms, distributed systems, data onboarding, exchange, discovery, and consumption.
• - **Cloud & infrastructure:** Cloud environments, on-premises environments, and cloud-native data services.
• - **Data technologies:** Spark, Kafka, Flink, NiFi, Hadoop/Cloudera, Databricks, Snowflake, Delta Lake, and streaming platforms.
• - **AI & emerging technology:** AI-enabled data platforms, AI-driven capabilities, agent-based architectures, agentic commerce, and governance guardrails.
• - **Data governance & security:** Data governance, information security, regulatory compliance, confidentiality, and integrity.
• - **Technical leadership:** Enterprise architecture strategy, technical vision, roadmaps, design patterns, and engineering best practices.
• - **Executive communication:** Translating complex technical and architecture concepts into clear business language.
• - **Stakeholder management:** Partnering with product, engineering, business, and executive stakeholders.
• - **Influence & decision-making:** Guiding technical and business decisions across organizational levels.
• - **Mentorship:** Developing and influencing global engineering teams.
• - **Collaboration:** Building inclusive, collaborative, high-performing teams.
• - **Agile delivery:** Agile, SAFe, and product-centric delivery models.

## Education & Experience

**Education**

- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience.

**Experience**

• - Principal-level or equivalent technical leadership experience in enterprise data architecture and platform strategy.
• - Extensive experience building large-scale data platforms, distributed systems, and enterprise integration solutions.
• - Experience across both on-premises and cloud environments.
• - Experience with modern data technologies and cloud-native data services.
• - Experience building reusable enterprise platforms for multiple products, teams, or business domains.
• - Experience integrating AI-driven capabilities into data platforms with appropriate governance and guardrails.
• - Experience leading architectural initiatives within Agile, SAFe, or product-centric environments.

## Work Arrangement & Schedule

• - **Location:** Arlington, Virginia, United States
• - **Work arrangement:** Onsite
• - **Employment type:** Full-time benefits are described in the source job description; the specific employment type is not otherwise stated.
• - **Expected weekly hours:** Not specified.
• - **Schedule flexibility:** Not specified.
• - **Weekend requirements:** Not specified.

## Compensation & Benefits

• - **Base salary:** $195,000–$323,000 USD for Arlington, Virginia.
• - The successful candidate may be eligible for an annual bonus or commissions depending on the role.
• - Base salary may vary based on factors including location, job-related knowledge, skills, and experience.
• - Medical, prescription drug, dental, vision, disability, and life insurance.
• - Flexible spending account and health savings account.
• - 16 weeks of new parent leave.
• - 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.
• - 401(k) with a company match.
• - Deferred compensation for eligible roles.
• - Fitness reimbursement or access to onsite fitness facilities.
• - Tuition reimbursement eligibility.

## Compliance / Additional Information

• - This role is **not eligible for Mastercard’s work authorization sponsorship**. Candidates must be eligible to work in the United States now and in the future without employer sponsorship.
• - Mastercard is a merit-based, inclusive, equal opportunity employer and considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disability or veteran status, or other characteristics protected by law.
• - Employees are responsible for information security when accessing Mastercard assets, information, and networks, including following security policies and practices, protecting confidentiality and integrity, reporting suspected security violations or breaches, and completing required security training.
• - Reasonable accommodations are available for applicants and candidates with disabilities.
• - Mastercard supports secure, simple, smart, and accessible digital payments across more than 200 countries and territories.