Staff Data Engineer

Hybrid, Austin-based role with Visa Technology and Operations LLC’s Value Added Services – Digital Marketing & Engagement organization. You will design and build the Visa data token platform and lead large-scale data pipeline and data platform initiatives in an agile environment. This Staff-level position combines technical impact with opportunities to mentor engineers and shape best practices across the team.

What you’ll be doing

• Design, build, and optimize large-scale data pipelines for both batch and real-time processing
• Develop and maintain distributed data systems that are highly available, scalable, and resilient
• Lead initiatives to process, transform, and manage structured and unstructured data across platforms
• Drive development of data platforms and data products for analytics, reporting, and machine learning use cases
• Partner with product, analytics, and business teams to translate requirements into scalable data solutions
• Architect solutions using Hadoop, Spark, and distributed data processing frameworks
• Build and optimize ETL/ELT pipelines, ensuring high data quality, reliability, and performance
• Implement automation, monitoring, and observability across the data pipeline lifecycle
• Lead proof-of-concept efforts to evaluate and adopt new data engineering technologies
• Influence data engineering best practices across data modeling, pipeline design, and governance
• Mentor engineers and foster a culture of continuous learning and accountability
• Architect and implement secure, robust, and scalable data platforms
• Drive innovation through experimentation, prototyping, and rapid iteration
• Ensure strong data governance, quality, and operational excellence
• Collaborate with cross-functional stakeholders to align on technical and business outcomes

Required qualifications

• 5+ years relevant work experience with a Bachelor’s Degree, or an alternative combination based on advanced degree or PhD experience as described below:
  • At least 2 years with an Advanced degree (e.g., Masters, MBA, JD, MD)
  • 0 years with a PhD
• 6+ years relevant work experience with a Bachelor’s Degree, or an alternative combination based on advanced degree or PhD experience as described below:
  • 4+ years with an Advanced degree (e.g., Masters, MBA, JD, MD)
  • Up to 3 years with a PhD
• Demonstrated leadership delivering high-quality, large-scale, enterprise-class applications
• Solid big data engineering background, including Hadoop, Apache Spark, Python, and SQL
• Experience with Docker and Kubernetes for containerization
• Proficiency creating and managing large-scale data pipelines and machine learning models
• Experience developing ETL processes, maintaining Spark pipelines, and productizing AI/ML models
• Proficiency with technologies including Kafka, Redis, Flink, TensorFlow, Triton, and AWS services
• Skilled in Unix/Shell or Python scripting and scheduling tools such as Airflow and Control-M
• Familiarity with Agile, TDD, CI/CD, and various databases
• Proven track record building reliable, scalable, and operable applications
• Ability to manage component security analysis and collaborate with security teams
• Strong work ethic with focus on immediate goals and experience as a technical leader
• Passion for mentoring and supporting junior engineers
• Excellent communication and interpersonal skills, and a strong team player

Technology focus

• Hadoop, Spark, ETL/ELT, distributed data processing frameworks, Python, SQL
• Docker, Kubernetes
• Kafka, Redis, Flink, TensorFlow, Triton
• AWS services
• Unix/Shell, Airflow, Control-M
• Agile, TDD, CI/CD, databases

Compensation and benefits

Estimated salary range: USD 137,200 - 219,700 per year. Salary may vary based on job-related factors including knowledge, skills, experience, and location.

• Medical
• Dental
• Vision
• 401(k)
• FSA/HSA
• Life Insurance
• Paid Time Off
• Wellness Program
• potential sales incentive payments (if applicable)
• bonus and equity

Travel, office, and work schedule

• Travel: 5-10% of the time
• Hybrid expectations: Visa requires at least 3 days in office; specific days will be confirmed by your Hiring Manager
• Work hours: varies based on department needs

Work environment

• Office setting
• Requires sitting and standing at a desk, communicating in person and by telephone
• Frequently operates standard office equipment such as telephones and computers

Education: Bachelor’s Degree.