Staff Data Engineer

Staff Data Engineer-Data Pipelines, Hadoop, Scala,spark,Kafka (6+yrs- 8 yrs)

• Bengaluru, India
• Full-time
• Job Family Group: Engineering and Technology

Company Description

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.

At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters — to you, to your community, and to the world.

Progress starts with you.

Job Description

About the Role

Visa is seeking a Staff Data Engineer to join its Data & AI Platform team. In this role, you will architect, design, and build scalable big data and enterprise platform solutions that power critical data, analytics, and AI capabilities across the organization, including tools and ecosystems such as Copilot, Cline, LLMs, Claude, and related AI-assisted engineering platforms.

The ideal candidate will bring deep technical expertise in Hadoop, Spark, Kafka, Big Data technologies, Java 8+, distributed systems, and API-driven application development, along with demonstrated strength in solution architecture, technical leadership, and mentoring.

Key Responsibilities:

• Architect, design, and develop scalable, high-performance data and AI platform solutions.
• Build and optimize batch and real-time data pipelines using Hadoop, Spark, and Kafka.
• Translate business and technical requirements into scalable architectures and enterprise-grade solutions.
• Develop and maintain applications and platform services using Java 8+, REST APIs, JSON, and container-based technologies.
• Lead complex technical initiatives spanning distributed systems, cross-functional technology teams, and business stakeholders.
• Establish and promote engineering best practices in performance, scalability, resiliency, security, and maintainability.
• Work within Agile development environments and CI/CD pipelines using tools such as Git, Maven, Jenkins, Triton, Chef, Sonar, Clover, JUnit, and Mockito.
• Champion shift-left quality practices, including performance testing and secure coding standards.
• Mentor engineers and provide technical leadership through design reviews, problem-solving, and architectural guidance.
• Leverage agentic coding tools and AI-assisted engineering practices to enhance developer productivity, code quality, and delivery speed.

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

Qualifications

Basic Qualifications:

5+ years of relevant work experience with a Bachelor’s Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD, OR 8+ years of relevant work experience.

Preferred Qualifications:

5+ years of relevant work experience with a Bachelor’s Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD, OR 8+ years of relevant work experience.

Experience supporting Data, Analytics, and AI/ML platforms. Familiarity with cloud platforms and container ecosystems.

Experience with observability, resiliency engineering, and performance optimization. Strong communication, collaboration, and stakeholder management skills.

Experience using GenAI tools, LLMs, Cline, Claude, and similar AI-assisted coding platforms for software development, code reviews, and engineering workflow optimization.

Additional Information

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.