Visa is building a next-generation Agentic AI and Data Platform to enable intelligent automation, adaptive workflows, and data-driven decision-making across our Risk and Identity services ecosystem.

As a Lead Data Engineer, you will serve as a strategic technical leader, architecting, scaling, and optimizing enterprise-wide data platforms. You will drive innovation, set technical direction, and mentor a high-performing team to deliver robust, secure, and high-quality data solutions that power business-critical analytics and applications across the organization.

Key Responsibilities

Technical Leadership & Strategy

• Define and drive the data engineering vision, strategy, and roadmap in alignment with business goals.
• Architect and oversee the design of complex, distributed data systems, ensuring scalability, reliability, and security.
• Establish and enforce technical standards, best practices, and governance for data engineering across teams.
• Advise on technical specifications and collaborate with product owners, business partners, and cybersecurity teams to clarify requirements and dependencies.

Team Leadership & Mentoring

• Lead, mentor, and grow a team of data engineers, fostering a culture of innovation, accountability, and continuous improvement.
• Conduct regular code and design reviews, promoting clean, efficient, and maintainable code.
• Champion professional development and knowledge sharing within the team.

Project & Stakeholder Management

• Own end-to-end delivery of large-scale data engineering projects, including prioritization, planning, and stakeholder management.

• Track external commitments and ensure timely delivery of features and enhancements.

• Identify and drive opportunities for process improvements and automation.

Technical Excellence & Innovation

• Resolve complex technical issues and make impactful decisions that shape the future of data engineering at the enterprise level.
• Lead the evaluation and adoption of emerging technologies (e.g., cloud platforms, streaming, ML/AI integration).
• Ensure production systems are robust, performant, and meet SLAs.
• Proactively identify and resolve bottlenecks.

Cross-Functional Collaboration

• Work closely with senior engineers, architects, and product managers to develop innovative solutions for new product development.
• Collaborate with business and analytics teams to deliver data products that unlock business value.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Basic Qualifications:
14 or more years of relevant work experience with a bachelor’s degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 14+ years of relevant work experience.

Preferred Qualifications
Proven experience architecting and leading enterprise-scale data engineering initiatives (Hadoop, Hive, Spark, Kafka, etc.).
Strong programming proficiency in Python, Java, or Scala.
Production-level experience architecting Hadoop, Spark, and Databricks data pipelines.
Hands-on experience with AWS or Azure (Glue, Synapse, Redshift, Delta Lake, S3).
Familiarity with Kafka, Airflow, Kubernetes, and containerized data services.
Deep expertise in cloud platforms (AWS, Azure, GCP) and associated services (EC2, S3, SageMaker, etc.).
Advanced proficiency in programming languages (Scala, Python, Java) and scripting (Unix/Shell, Python).
Understanding of RAG pipelines, vector databases, and AI data flows.
Experience designing data pipelines and APIs compatible with Model Context Protocol (MCP)-based agent frameworks, enabling seamless integration between AI agents, data services, and enterprise API
Strong background in data modeling, ETL/ELT, and optimization of big data pipelines.
Experience with CI/CD, automated testing, and DevOps tools (Jenkins, Artifactory, Git, Selenium, Chef).
Familiarity with RDBMS (MS SQL, DB2, Oracle) and visualization tools (Tableau, Power BI).
Demonstrated ability to lead teams, influence stakeholders, and deliver results in a fast-paced, global environment.
Excellent communication, leadership, and organizational skills.

Leadership Attributes:
Go-Getter: Executes decisively and thrives in complex, hybrid data environments.
Builder: Hands-on architect who delivers scalable, production-grade data systems.
Hustler: Operates with urgency and accountability across multiple technology stacks.
Entrepreneurial: Drives innovation in data architecture and modernization.
True North: Leads with integrity and alignment to Visa’s mission and long-term data strategy.
Lead by Example: Sets high standards of excellence and transparency.
Execute with Excellence: Ensures reliability, performance, and operational maturity across all data systems.

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.