Visa-posted 5 months ago
$226,900 - $354,500/Yr
Full-time • Senior
Hybrid • Foster City, CA
Credit Intermediation and Related Activities

Visa is rapidly expanding its Value-Added Services (VAS) product portfolio globally, with the VAS Architecture and Platform organization positioned at the intersection of diverse technologies, platforms, and solutions that drive this growth. We are seeking a Senior Director with deep expertise in data and machine learning system development and operations. This leader will play a crucial role in both strategic and tactical planning and execution, continuously advancing the vision and mission of the AI Platform. In this role, you will be a dedicated and versatile data engineering leader, capable of thriving in a fast-paced environment and contributing as an active member of Agile scrum teams. As a key member of the leadership team, you will shape the technical roadmap, introduce cutting-edge machine learning and system technologies, collaborate with development managers to address technical challenges, and partner with product and data science teams to streamline feature requests and model onboarding.

  • Lead the design, development, and deployment of scalable and secure data pipelines, platforms, and ML/AI infrastructure, leveraging cloud-native technologies and big data frameworks.
  • Oversee the integration of structured and unstructured data sources to support advanced analytics, machine learning, and AI initiatives.
  • Evaluate, implement, and champion new tools and technologies to improve productivity, scalability, and effectiveness of data engineering efforts.
  • Establish and enforce data engineering best practices, technical standards, governance, and quality standards, ensuring continuous improvement and technical excellence.
  • Ensure data security, privacy, compliance, system performance, scalability, and availability across all data engineering projects and platforms.
  • Define, monitor, and report on key performance indicators (KPIs) to measure the success and impact of data engineering activities.
  • Lead incident response, root cause analysis, and resolution for data platform issues, ensuring high availability and reliability.
  • Collaborate with cross-functional teams—including Data Science, Analytics, Product, Engineering, and project teams—to deliver robust data-driven business solutions and define technical roadmaps.
  • Mentor, coach, and grow a high-performing team of data engineers, fostering a culture of innovation, excellence, and continuous learning, oversee talent development and team pipeline evolution.
  • Partner with senior leadership to define, execute, and communicate the enterprise data strategy, represent the data engineering function in executive meetings and strategic planning sessions.
  • Develop and manage budgets, resource planning, and vendor relationships for data engineering initiatives.
  • Promote a data-driven culture by enabling self-service analytics and democratizing access to data across the organization.
  • 12+ years of relevant work experience with a Bachelor's Degree or at least 9 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 6 years of work experience with a PhD, OR 15+ years of relevant work experience.
  • Bachelor's or Master's degree in computer science, Engineering, or a related field.
  • 15-20 years of experience in data engineering, software development, or related technical roles.
  • Proven experience leading large-scale data engineering teams and projects in a complex enterprise environment.
  • Expertise in data architecture, ETL/ELT pipelines, data warehousing, and real-time data processing.
  • Hands-on experience with cloud platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark, Kafka, Hadoop).
  • Strong understanding of data modeling, data governance, and data quality frameworks.
  • Excellent communication and stakeholder management skills.
  • Track record of delivering high-impact data solutions that drive business outcomes.
  • Strong sense of ownership, urgency, and leadership abilities in an engineering environment in driving operational excellence and standard methodologies.
  • Master's, PhD in Computer Science or related technical discipline.
  • Experience in financial services, payments, or a highly regulated industry.
  • Experience working with Data and AI, designing, and building ML infrastructure to train or serve models.
  • Experience working on large open-source projects, preferably in the ML infrastructure domain like TensorFlow, Ray, JAX, PyTorch, Horovod.
  • Contributions to open-source data engineering tools or communities.
  • Medical
  • Dental
  • Vision
  • 401 (k)
  • FSA/HSA
  • Life Insurance
  • Paid Time Off
  • Wellness Program
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