Data Engineering Manager - ML Ops

Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

Sr. Manager, Data Engineering, MLOps

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Team Summary:

The Risk and Identity Solutions (RaIS) team provides risk management services for banks, merchants, and other payment networks. Machine learning and AI models are the heart of the real-time insights used by our clients to manage risk. Created by the Visa Predictive Models (VPM) team, continual improvement and efficient deployment of these models is essential for our future success. To support our rapidly growing suite of predictive models we are looking for engineers who are passionate about managing large volumes of data, creating efficient, automated processes and standardizing ML/AI tools.

Leadership & Management:

• Hire, retain, and grow high-performing, diverse engineering and data science teams.
• Lead with a client-focused mindset across organizations.
• Mentor and motivate high-performing teams of engineers, and tech leads to achieve critical business goals and KPIs.

Technical Leadership:

• Provide technical leadership/oversight to data engineers, and data scientists.
• Drive the architecture for key cross-team/cross-product development projects.
• Establish software development and data science best practices via examples and shipping code.
• Ensure engineering and data science excellence (quality, security, performance, scalability, availability, resilience).

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:

•  Degree (e.g. Masters, MBA, JD, MD) in Engineering or similar field of study 
• Strong technical knowledge and expertise in software engineering and data engineering to guide and support the team.
• Experience building and supporting scalable, reliable data solutions and AI/machine learning powered systems using modern big data and ML/AI technologies.

Preferred Qualifications:

• Comprehensive understanding of database design and management systems (both SQL and NoSQL), expertise in performance optimization, data security, data modelling etc. along with the ability to adapt new database technologies.
• Strong knowledge on AWS services such as S3, EC2, Lambda, EMR, Opensearch and having understood on machine learning services like Sagemaker is plus.
• Solid understanding of Big Data technologies, notably Hadoop for distributed data storage and Spark for large-scale data processing, enabling team to handle and analyze vast amounts of data efficiently.
• Good Understanding of practices like, CI/CD pipeline, version control systems (like Git), and containerization tools (like Docker).
• Having worked on MLOps solutions prior is a big plus
• Hands-on experience partnering with data scientists and can speak knowledgeably about the major machine learning paradigms, algorithms, software tools, infrastructure and workflow needs. Publications or presentations in recognized computing journals/conferences is a plus. 
• Payment industry experience is a plus.
• Familiarity with the associated open-source ecosystem (e.g., mlflow, ELK) is a plus. 
• Proficiency in a variety of machine learning algorithms and models like linear/logistic regression, random forest, boosting, neural networks 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.