Staff Data Engineer

Visa•Austin, TX

7d•$131,600 - $210,300•Hybrid

About The Position

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: Staff Data Engineers are expert problem-solvers and builders who design, implement, and improve software applications and systems. In this role, engineers spend a significant portion of their time coding, working hands-on with code, data, and modern tools—including AI-assisted development, cloud services, and automation frameworks—to deliver secure, scalable, and high-quality technology solutions that drive business outcomes in the fintech sector. They collaborate with cross-functional teams such as product managers, designers, data scientists, QA, operations, and compliance to translate business requirements into robust technical solutions, all while adhering to best practices, security standards, and regulatory requirements. 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.

Requirements

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 in designing and implementing data pipelines and large-scale data processing jobs.
Experience in writing, modifying, and reviewing high-quality, testable, and efficient code.
Experience in developing unit, integration, and end-to-end tests with a focus on automation.
Experience in building and maintaining CI/CD pipelines and deploying applications using containerization and orchestration tools.
Experience in monitoring applications in production and troubleshooting issues using observability tools.
Experience in integrating AI or ML services into applications, where applicable.
Experience in collecting and analyzing metrics to guide optimizations and improvements.
Experience in partnering with stakeholders to clarify requirements and ensure deliverables meet business needs.
Experience in applying secure coding practices and complying with regulatory standards.
Experience in solving data problems using data technologies (e.g., Hadoop, Hive, Kafka, Redis, NoSQL, RDBMS).
Experience in building and pushing code into production.
Experience in implementing and supporting real-time systems.
Experience in mentoring junior engineers and writing clear technical documentation.

Responsibilities

Act as a key participant in meetings with stakeholders to identify and clarify requirements and determine business needs.
Independently understand data ecosystems, security, privacy, and retention requirements to support business and product features.
Translate functional requirements into architecture designs for one or more components, leveraging existing architecture design patterns, and communicate these to Data Engineers.
Implement extensible, maintainable, and reusable code using appropriate coding patterns, guidelines, and best practices; participate in code reviews to ensure standards are followed.
Provide end-to-end ownership of data products or data pipelines, including mitigation of technical debt and documentation of errors or unexpected bugs.
Identify and conduct required testing for moderately complex use cases, including unit testing, coding standards, and security scans.
Build tools and standard automation processes to assist in transforming, managing, accessing, deploying, and monitoring data processes in batches and in real time.
Write queries to extract and compile raw data across end-to-end pipelines, and implement orchestration techniques to automate data extraction logic.
Ensure adherence to data management principles, governance, and tools to maintain data quality across multiple features.
Develop and update troubleshooting guidance and procedures for reviewing, addressing, and fixing advanced problems flagged by testing.
Manage software upgrades and server patches for security remediation where applicable.