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Lead Machine Learning Engineer- Data - job 7 of 20

The Data and Artificial Intelligence Platform group is a key component of Visa's Technology organization, providing the enabling technology and processes to handle Visa's data assets and deliver valuable information, products, and services to customers. Our team delivers secure, high-quality, and easy-to-use Visa core data assets, along with reliable and scalable data platforms.  Our platform operationalizes the delivery of AI and decision intelligence to ensure ongoing business value to Visa and our clients.

As a Lead Machine Learning Engineer- Data with expertise in Machine Learning and Data Engineering, you will drive innovation in developing purpose-fit data solutions using cutting-edge technologies. You will be responsible for executing a data strategy that leverages our data assets to drive innovation through data engineering and GenAI solutions, including developing a synthetic data engine. You will also guide and mentor junior engineers, ensuring security, scalability, performance, and reliability in all data solutions. As an individual contributor based in Foster City, California, USA you will be reporting to Sr. Director of Data as a Service (DaaS) team. This team is growing fast! Join us and be an integral part of the group that is at the leading edge of pioneering Data and AI.

What We Offer:

  • Exciting Challenges: We work at a scale rarely seen in the industry, solving complex data and AI problems across the entire stack, offering limitless opportunities to leverage and lead in this ever-growing field.

  • Teamwork and Fun: Each of us brings diverse and rich experiences to the team, enabling us to deliver much more than the sum of our parts and have fun at the same time.

  • Fantastic People: With strong leadership, you will have the opportunity to learn, collaborate, and deliver together with some of the best and most creative minds in the industry.

About the Role:

  • Lead the design and architecture of robust, scalable data engineering platforms and infrastructure, including data pipelines, data warehouses, and data lakes (on-prem and cloud-based).

  • Oversee the entire data lifecycle, from data acquisition and ingestion to transformation, storage, and analysis.

  • Develop a synthetic data engine to generate on-demand privacy enhanced synthetic data where actual production data cannot be used, ensuring scalability and compliance.

  • Build and experiment with modeling and scoring algorithms, including custom algorithms and packaged tools based on machine learning, analytics, and statistical techniques.

  • Champion the adoption of GenAI and Agentic AI technologies and develop strategies to integrate them into existing workflows or build new ones.

  • Ensure data security, privacy, governance, and compliance with all relevant regulations, and develop and implement auditable policies and procedures.

  • Lead and guide a high-performing data engineering and ML team, fostering a culture of innovation and continuous learning.

  • Partner with business stakeholders to understand their needs and translate them into actionable data-driven solutions.

  • Stay up-to-date on emerging data and AI trends and technologies.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Average salary estimate

$150000 / YEARLY (est.)
min
max
$120000K
$180000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Lead Machine Learning Engineer- Data, Visa

At Visa, we're proud to have a groundbreaking team within our Data and Artificial Intelligence Platform group, where innovation thrives, and creativity is paramount! As a Lead Machine Learning Engineer - Data based in Foster City, you will play a crucial role in shaping the future of data engineering and AI for our organization. Imagine leading the charge in developing purpose-fit data solutions using the latest cutting-edge technologies and methodologies. Your primary responsibility will be to execute our comprehensive data strategy, harnessing Visa's extensive data assets to inspire innovation through data engineering and GenAI solutions, notably creating a synthetic data engine to enhance privacy. You'll have the opportunity to mentor junior engineers, sharing your expertise while ensuring that all data solutions are secure, scalable, and reliable. Working alongside some of the brightest minds in the industry, you will be deeply involved in designing and architecting robust data platforms and overseeing the entire data lifecycle from acquisition to analysis. With a strong focus on compliance and governance, you'll help usher Visa into the future of data handling. Join us in this dynamic environment that encourages growth and celebrates diversity, teamwork, and fun. If you're excited about addressing complex data challenges and making a significant impact, we want to hear from you! Together, let's invest in the future of data at Visa!

Frequently Asked Questions (FAQs) for Lead Machine Learning Engineer- Data Role at Visa
What responsibilities does the Lead Machine Learning Engineer - Data at Visa have?

The Lead Machine Learning Engineer - Data at Visa is responsible for designing and architecting scalable data platforms, overseeing the entire data lifecycle from acquisition to analysis, and developing innovative solutions such as a synthetic data engine. You'll also mentor junior engineers and ensure data security, governance, and compliance with regulations.

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What qualifications are required for the Lead Machine Learning Engineer - Data position at Visa?

To excel as a Lead Machine Learning Engineer - Data at Visa, candidates should possess strong expertise in machine learning, data engineering, and experience with data lifecycle management. A relevant degree and a solid grasp of data security and privacy regulations are also essential for this role.

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How does Visa support the growth of its Lead Machine Learning Engineers?

Visa fosters professional growth by providing opportunities for mentorship, collaboration on innovative projects, and exposure to emerging technologies. You'll work alongside talented professionals and benefit from strong leadership that encourages continuous learning and teamwork.

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What technologies are used by the Lead Machine Learning Engineer - Data at Visa?

As a Lead Machine Learning Engineer - Data at Visa, you will work with various cutting-edge technologies in data engineering, machine learning, and AI, including platforms for building data pipelines, data lakes, modeling algorithms, and adopting GenAI and Agentic AI technologies to enhance workflows.

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What is the workplace culture like for a Lead Machine Learning Engineer - Data at Visa?

The workplace culture at Visa for a Lead Machine Learning Engineer - Data is vibrant and collaborative, emphasizing diversity, fun, and innovation. The team prides itself on creating an engaging environment that combines teamwork with the thrill of solving complex challenges, ensuring all voices are heard.

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Common Interview Questions for Lead Machine Learning Engineer- Data
Can you describe your experience with data lifecycle management?

In answering this question, focus on specific examples of how you've managed every stage of the data lifecycle, from acquisition and ingestion to storage and analysis. Highlight tools and technologies you've used, as well as your role in ensuring data quality and compliance.

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How do you approach designing scalable data pipelines?

Discuss your methodology for creating scalable data pipelines, including the technologies you prefer and the design principles that guide your choices. Mention previous projects where you successfully implemented scalable solutions and any challenges you overcame.

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Can you explain a machine learning project you've led?

Provide a detailed overview of a machine learning project, focusing on the objective, your role, the technologies used, and the outcomes. Highlight any innovative solutions or models you developed and the impact they had on the organization.

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What best practices do you follow to ensure data security and compliance?

Share specific practices you adhere to while leading data projects, emphasizing your understanding of industry regulations and security measures. Discuss how you've implemented frameworks or policies to maintain security and ensure compliance with laws.

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How do you mentor junior data engineers or scientists?

Detail your approach to mentorship, including techniques you use to support junior team members, such as providing constructive feedback, organizing training sessions, and fostering a collaborative learning environment.

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What is your experience with synthetic data generation?

Describe any projects where you have worked with synthetic data generation, emphasizing the techniques and technologies used, your understanding of its implications for privacy, and how you ensured the generated data met project needs.

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How do you stay current with emerging data and AI technologies?

Discuss your strategies for keeping updated with the latest trends in data and AI, such as attending conferences, reading research papers, participating in webinars, and networking with industry professionals.

Join Rise to see the full answer
Can you explain a time when you had to collaborate with business stakeholders?

Provide an example demonstrating effective collaboration with business stakeholders. Highlight how you translated business needs into actionable data-driven solutions and the positive results of your collaboration.

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How do you handle unexpected challenges in data projects?

Discuss your problem-solving process when faced with unexpected challenges in data projects. Include specific examples where you adapted your approach and the outcomes, emphasizing resilience and flexibility.

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What role do you think GenAI plays in the future of data engineering?

Share your perspective on the future landscape of data engineering, with an emphasis on GenAI technologies. Discuss potential applications, the value they bring to businesses, and how you envision integrating these technologies in data workflows.

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Visa Inc. operates as a payments technology company worldwide. The company facilitates commerce through the transfer of value and information among consumers, merchants, financial institutions, businesses, strategic partners, and government entiti...

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Full-time, hybrid
DATE POSTED
April 3, 2025

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