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: Visa's Data Platform organization builds and operates foundational data, compute, streaming, workflow, low-latency data access, and secure data services that power critical Visa products, analytics, and application platforms. We are modernizing the platform with an agent-first engineering model where strong software engineering fundamentals, distributed systems thinking, and responsible use of AI/LLMs come together to improve developer productivity, platform reliability, and speed of delivery.  

We are looking for a hands-on Software Engineer in the Data Engineering job family who can design, build, test, and operate high-quality platform capabilities across modern data infrastructure. The ideal candidate has strong fundamentals in computer science, data structures, algorithms, databases, APIs, distributed systems, concurrency, reliability, and secure software development. The candidate should also be a champion of agentic AI development with practical understanding of LLMs, development prompting, context engineering, AI-assisted coding, automated testing, and human-in-the-loop review practices.  

In this role, you will contribute to Visa's next-generation data platform across Spark compute, streaming services such as Kafka and Flink, low-latency distributed key-value services, workflow orchestration with Airflow and Temporal, and secure data services for application-level encryption and decryption. You will help create platform services that are reliable, secure, observable, easy to use, and designed for AI-native engineering workflows.  

Essential Functions  

• Design, develop, test, deploy, and operate software for Visa's modern Data Platform, with focus on scalable, secure, and highly reliable platform services.  

• Contribute to backend services, APIs, SDKs, automation, developer tooling, platform integrations, data pipelines, and operational workflows used by internal engineering teams.  

• Work across core platform areas including Spark compute, Kafka/Flink streaming, low-latency distributed key-value services, Airflow/Temporal workflow orchestration, and secure data services.  

• Write clean, maintainable, well-tested code using languages such as Java, Scala, Python, or similar platform engineering technologies.  

• Apply strong engineering fundamentals in data structures, algorithms, object-oriented design, distributed systems, databases, networking, concurrency, performance tuning, and failure handling.  

• Build software that conforms to Visa's standards for security, quality, performance, resiliency, privacy, compliance, and operational readiness.  

• Participate in design reviews, code reviews, architecture discussions, production readiness reviews, and operational retrospectives.  

• Use agentic AI and LLM-based development practices responsibly to improve the engineering lifecycle, including requirements clarification, design exploration, code generation, test generation, documentation, review assistance, incident analysis, and knowledge capture.  

• Create and improve development prompts, reusable context packs, agent workflows, evaluation criteria, and guardrails that help engineers use AI effectively while preserving human accountability for design and production quality.  

• Develop measurable productivity and quality improvements from AI-assisted engineering practices, including metrics such as cycle time, review time, test coverage, defect escape rate, documentation quality, and operational toil reduction.  

• Automate repetitive engineering and operational tasks through scripts, tools, CI/CD enhancements, self-service workflows, and intelligent engineering assistants.  

• Troubleshoot complex platform issues across services, data flows, compute engines, workflow orchestration, dependencies, infrastructure, and application integrations.  

• Contribute to service reliability through observability, logging, metrics, alerting, SLOs, runbooks, capacity planning, performance testing, and safe rollout/rollback practices.  

• Collaborate with architects, product owners, engineering managers, project managers, tech leads, security partners, and application teams to translate platform needs into well-designed technical solutions.  

• Stay current with trends in distributed data systems, cloud-native platform engineering, secure engineering, LLMs, agentic AI, prompt engineering, context engineering, and AI-assisted software delivery.  

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

Qualifications

Basic Qualifications  

• 1 or more years of relevant work experience with a Bachelor's Degree, or an Advanced Degree such as a Master's, MBA, JD, MD, or PhD.  

• Hands-on software development experience in Java, Scala, Python, or comparable backend/platform engineering languages.  

• Strong computer science fundamentals, including data structures, algorithms, object-oriented design, databases, APIs, operating systems, networking, and concurrency.  

• Experience building or supporting backend services, data services, distributed systems, APIs, automation, or platform engineering capabilities.  

• Understanding of software engineering practices including unit testing, integration testing, CI/CD, code reviews, secure coding, documentation, and production support.  

• Practical exposure to generative AI or LLM-assisted development, including prompt usage, code assistance, test generation, documentation, or engineering productivity use cases.  

Preferred Qualifications         •        1 or more years of software engineering experience in data platform, distributed systems, backend services, streaming, workflow orchestration, or developer platform domains.         •        Experience with Apache Spark, Kafka, Flink, Airflow, Temporal, distributed key-value stores, data pipelines, metadata services, or secure data access patterns.         •        Experience designing scalable and resilient services with clear APIs, strong observability, automated tests, and production readiness controls.         •        Working knowledge of SQL and NoSQL data stores, data modeling, schema evolution, event-driven architectures, and large-scale data processing patterns.         •        Experience with containerization, Kubernetes, CI/CD pipelines, infrastructure automation, monitoring tools, and service reliability practices.         •        Practical understanding of LLM concepts such as tokens, context windows, embeddings, retrieval-augmented generation, tool/function calling, evaluation, hallucination risk, and guardrails.         •        Hands-on experience with agentic AI development patterns, including coding agents, workflow agents, prompt templates, context engineering, model evaluation, AI-assisted test generation, and human approval checkpoints.         •        Ability to create high-quality development prompts and context packages that help AI tools understand requirements, architecture, coding standards, APIs, test expectations, and operational constraints.         •        Demonstrated ability to use AI tools to improve engineering productivity while maintaining security, privacy, compliance, code quality, and engineering accountability.         •        Strong debugging and problem-solving skills across application code, platform services, runtime behavior, dependency failures, performance bottlenecks, and distributed system issues.         •        Ability to communicate technical ideas clearly, document designs, collaborate across teams, and influence engineering practices through examples, tools, and measurable outcomes.

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.