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Data Engineer - Sr. Consultant level- Core Data Assets - job 11 of 21

The Data and Artificial Intelligence Platform group is a key component of Visa 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 as a service, along with reliable and scalable data platforms, enabling Visa and our partners to rapidly and efficiently innovate data-driven business products and services to lead the digital payment industry. Our application development is on the cutting edge of technology, and we are innovative leaders within our industry.

As a Data Engineer - Sr. Consultant level, you will play a key role in the innovation, design, and development of comprehensive Acquirer bundling and underwriting data pipeline solutions. These solutions will feed the data for feature built-in automated scoring models and customizable risk criteria, reporting, Data Analytics and Data delivery services for VISA’s Customers. In this individual contributor role, you will be responsible for creating and executing a data strategy that leverages our data assets, including developing a synthetic data engine, to drive innovation through data engineering and GenAI solutions.


Essential Functions:

  • Design, coding and testing of data models by mining and building data pipelines, ensuring data quality and integrity by implementing data validation, cleansing, and enrichment processes, Monitoring data pipelines, systems, and infrastructure to ensure they are running smoothly.
  • Implement the set of services needed to release AI and data science models capable of working with terabytes of data. This includes model related features like one time and ongoing automatic model training, deploying, and monitoring models, as well as platform related features such as model repository, feature stores, secure data access layer, encryption, decryption etc..
  • Design and develop fine-tune conceptual, logical, and physical data models to map our data requirements into database structures.
  • Provide technical leadership for efforts around tooling and infrastructure that enable teams to efficiently complete and maintain data engineering projects.
  • Work and partner with product delivery teams to fully implement the proof of concept and early product in Visa services and products.
  • Champion innovation across organizations and industries as an expert in the subject, either by providing consulting or by contributing to technology talks and presentations.
  • Present technical solutions, capabilities, considerations, and features in business terms. Effectively communicate status, issues, and risks in a detailed 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.

Average salary estimate

$140000 / YEARLY (est.)
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$120000K
$160000K

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What You Should Know About Data Engineer - Sr. Consultant level- Core Data Assets, Visa

As a Data Engineer - Sr. Consultant with Visa in Foster City, you will be stepping into a dynamic role at the heart of our Data and Artificial Intelligence Platform group. This isn't just another job; it's an opportunity to innovate and make significant contributions to the digital payment ecosystem. Your mission will be to design, develop, and manage comprehensive data pipeline solutions that are vital for our feature-rich automated scoring models and customizable risk criteria. Imagine being the architect of a synthetic data engine, complete with high-quality data assets that's at the forefront of data engineering and GenAI solutions. You’ll be challenged to ensure the integrity and quality of our data by implementing extensive validation and cleansing processes. With your expertise, you will monitor systems closely to ensure seamless operations. This role also offers you the chance to lead technical initiatives around data engineering tools and infrastructure, driving efficiency across teams. As you collaborate with product delivery teams, you will see your concepts evolve into viable products while championing innovation within Visa and beyond. Your ability to convey complex technical solutions in approachable business terms will be invaluable, as will your passion for presenting at industry events. This hybrid position allows you the flexibility to work both remotely and in the office, affording you the ideal balance for productivity and collaboration. If you're ready to make your mark in the digital payment industry, we want to hear from you!

Frequently Asked Questions (FAQs) for Data Engineer - Sr. Consultant level- Core Data Assets Role at Visa
What are the primary responsibilities of a Data Engineer - Sr. Consultant at Visa?

As a Data Engineer - Sr. Consultant at Visa, you'll take on various responsibilities that significantly impact our data strategy. You'll design and develop data pipeline solutions crucial for scoring models and risk criteria. Your role involves ensuring data integrity through validation processes and monitoring data systems. Additionally, you will lead efforts in implementing AI and data science models while collaborating with product delivery teams to bring your innovations to life.

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What skill set is required for the Data Engineer - Sr. Consultant position at Visa?

To excel as a Data Engineer - Sr. Consultant at Visa, candidates should bring a strong foundation in data modeling, data pipeline construction, and data quality assurance. Proficiency in machine learning concepts and familiarity with AI model deployment are also essential. Strong technical leadership skills and the ability to communicate complex solutions effectively in business terms are vital for engaging and collaborating with various teams.

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What is the importance of the synthetic data engine in the Data Engineer - Sr. Consultant role at Visa?

The synthetic data engine you'll develop as a Data Engineer - Sr. Consultant at Visa is crucial for leveraging our data assets to foster innovation. This engine allows for the creation of high-fidelity data that can be used for testing and refining our models without exposing real customer data, thus strengthening data privacy practices while driving analytical efficiency.

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What kind of projects can a Data Engineer - Sr. Consultant expect to work on at Visa?

As a Data Engineer - Sr. Consultant at Visa, you'll embark on exciting projects focusing on creating and enhancing data pipelines that support automated scoring models and risk assessments. You'll be involved in cutting-edge AI solutions and collaborate on building tools and infrastructure, which serve to make data engineering projects more effective and efficient for product delivery.

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What does the career growth look like for a Data Engineer - Sr. Consultant at Visa?

At Visa, a Data Engineer - Sr. Consultant can expect substantial career growth opportunities. The role provides a platform to build technical leadership capabilities, contribute to innovative projects, and participate in industry-leading discussions. This exposure can pave the way for advancement into senior leadership roles within technology or data engineering, depending on your career aspirations.

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Common Interview Questions for Data Engineer - Sr. Consultant level- Core Data Assets
Can you describe your experience in building data pipelines?

In responding to this question, highlight specific examples of data pipelines you've designed or improved. Discuss the technologies used, your approach to ensuring data quality, and how you monitored the pipeline's performance. Clear communication about the results achieved will demonstrate your ability to impact data engineering positively.

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How do you ensure data quality and integrity in your projects?

Discuss the various validation methods and data cleansing processes you employ. Emphasize the importance of data integrity in influencing business decisions and the tools you use to achieve compliance with these standards. Mention any metrics you track to measure data quality over time.

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What challenges have you faced when implementing machine learning models?

Share specific instances where you encountered challenges, such as data availability or model accuracy issues. Explain the steps taken to overcome these challenges and the lessons learned from the experience. This will show your problem-solving skills and resilience in the face of obstacles.

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Can you explain how to deploy an AI model effectively?

Articulate the steps you take in deploying an AI model, from initial development to version control and monitoring. Include any frameworks or platforms you prefer, and emphasize the importance of setting up infrastructure to support ongoing model training and evaluations. Collaborating with teams during deployment is also a key aspect to touch upon.

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What tools and technologies are you most comfortable using in data engineering?

List the programming languages, frameworks, and architecture tools you are familiar with, such as Python, SQL, or cloud platforms like AWS and Azure. Be ready to discuss how you've used these tools in past projects and any recent technologies you've been learning to ensure you remain up-to-date.

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How do you stay current with the latest trends in data engineering?

Mention your strategies for keeping up with industry trends, such as following key thought leaders, engaging in online communities, attending conferences, or taking relevant courses. This underscores your passion for continuous learning and improvement, which is vital in the fast-evolving tech landscape.

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Describe a time when you had to work with cross-functional teams.

Provide an example that showcases your teamwork and communication skills. Discuss how you liaised with product and technology teams to align goals and resolve any conflicts or challenges. Highlight the importance of understanding different perspectives in driving successful project outcomes.

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What methods do you use for monitoring and optimizing data systems?

Explain the monitoring tools or software you typically use to oversee data systems and how you identify areas for optimization. Emphasize the importance of ongoing performance assessments and proactive adjustments to ensure the effectiveness and efficiency of the data systems.

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How do you balance innovation with practical implementation in projects?

Discuss your approach to innovation while ensuring practical results. Share examples of how you've encouraged creative thinking in your team but also guided them towards achievable outcomes. This balance is crucial in a data engineering role at Visa, where pushing boundaries must align with business objectives.

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What role does documentation play in your data engineering projects?

Highlight the vital importance of documentation in providing clarity to your work and ensuring reproducibility. Discuss how you maintain documentation throughout the project lifecycle, facilitating easier onboarding for new team members and enhancing communication across different stakeholders.

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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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