Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

A Principal Data Engineer in the VAS PD (Value Added Services, Product Development) team under Digital Marketing and Engagement (DME) at Visa leads the architecture, design, and delivery of large-scale marketing data platforms and advanced data products. This strategic role focuses on building new value-added digital engagement products and enhancing marketing capabilities for Visa's clients globally.

Key Responsibilities:

• Architect, design, and deliver high-performing, extensible, and reusable data engineering systems that enable real-time and batch marketing analytics and engagement solutions at scale.
• Define technical standards, frameworks, and best practices for resilient and secure data pipeline development, ensuring adherence to all compliance, privacy, and security requirements for marketing and customer engagement datasets.
• Build and maintain robust ETL and ELT processes and data marts, leveraging big data and cloud technologies such as Spark, Hive, Hadoop, Kafka, AWS, and Azure.
• Deliver and monitor quality, completeness, and performance of marketing data platforms through instrumentation, benchmarking, and automated testing.
• Transform Visa’s digital offerings by integrating AI, ML, and GenAI capabilities for next-level campaign optimization, personalization, and customer loyalty measurement.
• Lead and influence multiple teams with a culture of innovation and drive for engineering excellence, mentoring and developing talent to sustain high-functioning, purpose-driven teams.
• Collaborate cross-functionally with product owners, business partners, and cybersecurity experts to clarify business requirements and translate them into scalable technical solutions for global digital engagement.
• Explore, map, and negotiate access to new data sources. Champion a data-driven culture through training, knowledge sharing, and internal documentation.
• Continuously stay ahead of emerging trends, industry best practices, and innovative data technologies to strengthen the competitiveness of Visa’s DME value-added products.

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager. ​

Qualifications

Basic Qualifications:
12 or more years of work experience with a Bachelor’s Degree or at least 10 years of work experience with an Advanced degree (e.g. Masters/MBA /JD/MD), or a minimum of 5 years of work experience with a PhD

Preferred Qualifications:
15 or more years of experience with a Bachelor’s Degree or 12 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, or MD), PhD with 9+ years of experience
Bachelor’s degree with twelve or more years of experience, or a Master’s/PhD with relevant experience in data engineering, computer science, or related fields.
Strong hands-on experience with big data platforms, distributed computing, real-time systems, and open-source technologies relevant to analytics and engagement (for example, Hadoop, Spark, Flink, Kafka, Hive).
Hands-on coding and production deployment expertise in Python, Java, SQL, Scala, Go, or C.
Track record integrating AI, ML, and GenAI into analytics and marketing platforms at scale.
Deep understanding of data architecture, pipeline optimization, testing, monitoring, and data governance for marketing and consumer engagement applications.
Previous experience building and scaling enterprise-class, high-volume transaction systems is highly valued.
Demonstrated leadership and ability to influence, develop, and collaborate across global teams.
Prefer prior exposure to payments, fintech, marketing, or customer engagement platforms.
Additional Skills & Attributes
Excellence in stakeholder management, agile project delivery, and innovation.
Competence with cloud-native data tools, CI/CD automation, and modern DevOps practices.
Analytical mindset, problem-solving ability, and strategic vision for continuous product evolution.

Additional Information

Work Hours: Varies upon the needs of the department.

Travel Requirements: This position requires travel 5-10% of the time.

Mental/Physical Requirements: This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.

U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is 230,500.00 to 334,700.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.