Staff Data Engineer
2 months ago
About this Team:
The AI Experimentation Platform (AIEP) team, a key component of the Data and AI Platform (DAP) technology organization within Visa, is at the forefront of harnessing the power of Artificial Intelligence (AI) to drive strategic growth and operational efficiency. The team is dedicated to developing an advanced platform that fosters technological innovation and delivers impactful solutions. This dedicated team is an integral part of Visa's commitment to harnessing AI's power, reflecting the company's forward-thinking approach to technological innovation. By creating an environment that fosters AI experimentation, they are paving the way for Visa's future growth and continued success.
As a Staff Data Engineer, you will have the unique chance to make a direct and meaningful impact by delivering solutions that powers AI systems. You will design, enhance, and build solutions dealing with the next generation AI/ML and GenAI technology and be an agent of transformation. We deliver and support strategic goals and have a lasting impact on our enterprise. We aim to stay ahead of the curve adapting to the advancement of AI and ML and keep our business miles ahead of our competitors.
Essential Functions:
Collaborate with project team members (Product Managers, Architects, Analysts, Engineers, Project Managers, etc.) for development and implementation of new data and machine learning driven business solutions and platforms.
Drive development effort End-to-End for on-time delivery of high-quality solutions that conform to requirements, conform to the architectural vision, and comply with all applicable standards.
Collaborate with senior technical staff and PM to identify, document, plan contingency, track and manage risks and issues until all are resolved.
Present technical solutions, capabilities, considerations, and features in business terms.
Effectively communicate status, issues, and risks in a precise and timely manner.
This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.
Qualifications
Basic Qualifications:
6+ years of relevant work experience with a Bachelor’s Degree or Advanced degree (e.g. Masters, MBA, JD, MD) or PhD, OR 8+ years of relevant work experience.
Preferred Qualifications:
6-8 years of relevant work experience with a bachelor’s degree or Advanced degree (e.g. Masters/MBA/JD/MD/PhD)
Experience programming in at least one or more in Java, Python, Scala and Go
Strong understanding of algorithms and data structures
Experience in building and supporting scalable, reliable data solutions leveraging Big Data and latest distributed computing technology stack.
Relevant work experience solving data problems using data technologies (e.g., Hadoop, Hive, Kafka, Redis, NoSQL, RDBMS).
Experience implementing and supporting real-time systems.
Hands-on experience and/or academic background developing systems for the machine learning lifecycle: data preprocessing and feature extraction, model training and evaluation, and deployment and monitoring.
Hands-on experience and/or academic background partnering with data scientists and can speak knowledgeably about the major machine learning paradigms, algorithms, software tools, infrastructure and workflow needs.
Knowledge and experience working on Single Page Applications development using Angular or similar framework is a plus.
Publications or presentations in recognized computing journals/conferences is a plus.
Payment industry experience is a plus.
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.
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