Sr. Data Engineer

• About Us
• 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

• Job Summary
• The Senior Data Engineer will design, develop, and operate scalable data and software platforms that enable intelligent digital experiences and AI-powered solutions. The successful candidate will collaborate with product managers, architects, software engineers, data scientists, cybersecurity partners, and business stakeholders to identify requirements and deliver secure, reliable, and production-ready capabilities.

The role requires strong data and software engineering fundamentals, combined with practical experience applying Generative AI and agentic technologies to enterprise use cases. The Senior Data Engineer will create and document technical designs, evaluate architectures and technology choices, build reusable services and data components, and contribute throughout the development and operational lifecycle.

The role also requires modern AI engineering fluency. Candidates should be comfortable using AI-assisted development environments, coding agents, enterprise copilots, and intelligent engineering tools throughout the software development lifecycle. This may include tools and capabilities such as Claude Code, Codex, GitHub Copilot, Copilot Studio Agents, AI-assisted IDE workflows, autonomous coding agents, and enterprise AI platforms.

Key Responsibilities:

Data Engineering & Platform Development:

• •Design, develop, and maintain scalable data platforms, pipelines, APIs, integrations, and backend services supporting Digital Marketing & Engagement solutions.
• •Build and operate secure, resilient, and observable systems supporting real-time, streaming, and batch processing workloads.
• •Develop reusable frameworks, services, and technical accelerators that improve platform capabilities, engineering efficiency, and scalability.
• •Collaborate with product, engineering, architecture, and business stakeholders to deliver high-quality technical solutions.

Generative AI & Agentic Solutions:

• •Build and integrate GenAI-powered applications, AI agents, and intelligent workflows that drive automation, personalization, insight generation, and productivity improvements.
• •Implement agentic architectures utilizing retrieval, tool calling, workflow orchestration, memory, and human-in-the-loop patterns.
• •Develop integrations with enterprise systems, APIs, data sources, and AI platforms using modern protocols and interoperability standards such as MCP.
• •Evaluate and continuously improve AI solution quality, reliability, safety, and effectiveness through testing, monitoring, and feedback mechanisms.

Responsible AI, Governance & Optimization:

• •Design and implement guardrails, governance controls, and security mechanisms for AI-powered applications and agents.
• •Establish controls to mitigate risks such as prompt injection, unauthorized data access, unsafe tool usage, hallucinations, and policy violations.
• •Optimize token usage, model selection, latency, throughput, and operational costs while maintaining solution quality and user experience.
• •Implement monitoring, observability, telemetry, and evaluation frameworks to support enterprise-grade AI operations.

AI-Assisted Engineering & Innovation:

• •Leverage AI-assisted development tools, coding agents, and intelligent engineering platforms throughout the software development lifecycle.
• •Validate AI-generated artifacts to ensure correctness, maintainability, security, compliance, and production readiness.
• •Drive adoption of modern engineering practices utilizing autonomous coding, automated testing, AI-assisted troubleshooting, and intelligent software delivery workflows.
• •Stay current with emerging technologies, frameworks, and industry trends in data engineering, Generative AI, and agentic systems.

Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.

Qualifications

Basic Qualifications:

Core Engineering:

• •2+ years of relevant work experience and a Bachelor's degree, OR 5+ years of relevant work experience.
• •Strong programming skills in Java, Python, or similar languages.
• •Experience building scalable data platforms, APIs, microservices, and cloud-native applications.
• •Experience with distributed systems, event-driven architectures, and streaming technologies such as Kafka.
• •Experience with CI/CD, automated testing, observability, and production support.
• •Strong understanding of data engineering, integration, governance, and platform architecture.

AI Engineering:

• •Experience building or integrating Generative AI and LLM-powered applications.
• •Experience with Retrieval-Augmented Generation (RAG), vector search, embeddings, semantic retrieval, and context management.
• •Understanding of agentic AI concepts, tool calling, workflow orchestration, and AI application design patterns.
• •Experience implementing AI guardrails, governance, security controls, and responsible AI practices.
• •Experience evaluating and optimizing AI solution quality, latency, token consumption, and cost.

AI-Assisted Development:

• •Experience using AI-assisted development platforms and coding agents such as GitHub Copilot, Copilot Agents, Claude Code, Cursor, Windsurf, or equivalent tools.
• •Experience applying AI-assisted workflows for design, development, testing, debugging, code review, and documentation.
• •Strong analytical, problem-solving, and collaboration skills.

Preferred Qualifications:

• •3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD).
• •Experience with LangChain, LangGraph, Semantic Kernel, Spring AI, CrewAI, AutoGen, or equivalent AI frameworks.
• •Experience with Model Context Protocol (MCP), Agent-to-Agent (A2A) communication, and agent interoperability standards.
• •Experience with AgentOps, LLMOps, or AI platform engineering practices.
• •Experience with vector databases, knowledge graphs, enterprise search, and context engineering.
• •Experience with model evaluation frameworks, benchmarking, and AI observability.
• •Experience building AI and data solutions on Azure, AWS, or Google Cloud.
• •Experience in Digital Marketing, Customer Engagement, Personalization, or MarTech platforms.
• •Experience mentoring engineers and influencing technical direction across teams.

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.