Senior 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

Visa’s Technology Organization is a community of problem solvers and innovators, reshaping the future of commerce. We operate one of the world’s most advanced payment processing networks, enabling secure, reliable, and scalable transactions across millions of merchants, financial institutions, and consumers globally.

Our teams build and operate complex distributed systems at massive scale, solving challenges across payment flows, real-time data processing, cybersecurity, and next-generation digital platforms.

Within this, Value Added Services (VAS) – Digital Marketing is a key growth area for Visa, focused on building differentiated, data-driven solutions that extend the value of the Visa network beyond payments.

About the Team:

You will join a high-performing engineering team building GenAI-powered platforms and applications that enable innovation across Visa’s technology ecosystem.

The team focuses on:

Developing intelligent, AI-driven applications powered by large language models

Integrating generative AI capabilities into enterprise platforms and workflows

Building scalable systems that combine AI, data, and distributed architectures

Enabling automation, developer productivity, and intelligent decision-making

While these capabilities rely on strong data foundations, the primary focus is on applying AI and generative AI to solve real-world business problems at scale, with enterprise-grade security and reliability.

Job Summary

Sr. Data Engineers are responsible for collaborating with stakeholders, including product teams, business partners, and cybersecurity, to identify and clarify requirements for data-driven features and products. They independently understand the data ecosystem, security, privacy, and retention requirements necessary to support business and product features. Sr. Data Engineers create and document technical designs for components, identify systems, architectures, tools, and storage needs, and present technical solutions to peers. They stay current with market trends and industry dynamics, applying this knowledge to drive innovation and ensure the safety and security of product components.

• All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work.
• Key Responsibilities:

• •Collaborate proactively with stakeholders to clarify requirements and identify key product stakeholders.
• •Review technical requirements, escalate potential design issues, and create component designs and documentation.
• •Implement code, apply coding patterns and best practices, and adhere to security requirements.
• •Participate in code reviews, apply feedback, and take ownership of data products or pipeline components.
• •Conduct unit testing, coding standards, and security scans; participate in user acceptance testing.
• •Build tools and simple automation processes for transforming, managing, accessing, deploying, and monitoring data processes.
• •Create queries to extract and compile raw data, implement orchestration techniques, and validate data quality.
• •Ensure adherence to data management principles, governance, and performance monitoring protocols.
• •Contribute to troubleshooting guidance and procedures for reviewing and fixing problems flagged by testing.
• •Address routine client requests requiring technical knowledge and support software upgrades and server patches for security remediation.

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

Qualifications

Basic Qualifications:

2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience

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)
• •Strong core programming skills in Java, Python, or similar languages

Experience building and operating microservices-based architectures and APIs

Experience working with real-time data streaming or event-driven systems

Experience working with cross-functional teams to clarify requirements and define technical solutions

Experience designing and documenting technical components for data platforms, services, or applications

Experience writing production-grade code and applying coding standards, security practices, and testing methodologies

Experience conducting unit testing and participating in integration or user acceptance testing

Experience building automation tools and frameworks supporting data processing or application workflows

Experience working with data extraction, transformation, and querying techniques across large datasets

Experience ensuring system reliability through data quality validation, monitoring, and performance tuning

Experience troubleshooting and resolving issues in distributed systems, data pipelines, or backend services

Experience supporting production systems, including software upgrades, maintenance, and security remediation

Experience working with Generative AI systems, including integrating large language models into applications

Hands-on experience building applications using LLM providers such as OpenAI, Anthropic, or similar platforms

Familiarity with modern GenAI development practices, including prompt design, context management, and orchestration patterns

Experience with backend platforms, APIs, and microservices architectures supporting AI-driven applications

Experience with streaming frameworks (Kafka)

Experience presenting technical designs and solutions to engineering peers

Experience staying current with emerging trends in AI, GenAI, and distributed systems, and applying them to real-world use cases

Experience participating in code reviews and mentoring engineers on best practices

Strong problem-solving skills and ability to work in fast-paced, ambiguous environments

AI Engineering:

Familiarity with concepts such as:

Prompt engineering

System prompts and instruction design

Retrieval-augmented generation

Vector search

Embeddings

Tool calling

Function orchestration

Context management

Agent memory

Evaluation datasets

Model benchmarking

Feedback loops

A2A and MCP Protocols

Experience with agentic AI frameworks or tools such as:

LangChain

LangGraph

Model Context Protocol Servers

Spring AI

OpenAI and Anthropic SDKs

Vector databases

Knowledge graphs

Model evaluation frameworks

Ability to evaluate AI outputs objectively and improve quality, safety, reliability, latency, and cost.

Experience using commercial or open-source AI models and APIs.

Demonstrated ability to use AI tools in everyday work for coding, debugging, research, documentation, testing, or productivity improvement

Software Engineering:

Strong programming ability in one or more languages such as:

Java

Python

Experience building backend services, APIs, data pipelines, integrations, or cloud-native applications.

Familiarity with web applications, distributed systems, databases, CI/CD pipelines, logging, monitoring, and automated testing.

Ability to write clean, maintainable, secure, and production-ready code.

Experience participating in design reviews