Data Engineer - Sr. Consultant level- Core Data Assets - job 9 of 21

As a Data Engineer - Sr. Consultant level at Visa, key responsibilities include designing, coding, and testing data models while building and maintaining data pipelines. You will ensure data quality and integrity through various validation and cleansing processes. Additionally, you will implement services essential for AI and data science models, collaborate with product teams on proof-of-concept implementations, and champion innovation within the organization.

To qualify for the Data Engineer - Sr. Consultant level role at Visa, candidates typically need a strong background in data engineering, including experience with data pipeline development and data modeling. A solid understanding of AI models and data governance is essential, along with proficiency in programming languages relevant to data processing, such as Python, SQL, or Java. Strong communication skills for presenting technical solutions are also a must.

The data pipeline solutions crafted by the Data Engineer - Sr. Consultant level at Visa are critical for creating seamless access to data supporting automated scoring models and customizable risk criteria. These solutions play a vital role in improving Visa's services and products by allowing for rapid innovation and informed data-driven decision-making, ultimately enhancing the company’s position in the digital payment industry.

The hybrid work model for the Data Engineer - Sr. Consultant level position at Visa allows employees the flexibility to alternate between remote work and office presence. Employees are expected to collaborate in the office 2-3 days a week, which fosters teamwork while also providing the convenience of remote work based on business needs and personal preferences.

The Data Engineer - Sr. Consultant level supports innovation at Visa by designing and executing strategies that leverage data assets. By developing cutting-edge data engineering and GenAI solutions, this role influences product development and enhances the overall efficiency of services offered by Visa, ensuring the company remains a leader in the fast-evolving payments landscape.

In answering this question, reflect on specific projects where you've designed data models. Detail the steps you took, the tools you used, and how those models supported business objectives. Highlight your understanding of conceptual, logical, and physical data structures and how you've ensured data accuracy and integrity.

Discuss your approach to ensuring data quality, including validation, cleansing, and enrichment processes. Provide examples of how you've implemented these practices in previous roles, emphasizing your attention to detail and commitment to delivering high-quality data solutions.

Be prepared to list the programming languages and tools you are familiar with, especially those relevant to data engineering, such as Python, SQL, or Apache Spark. Explain how you’ve used these technologies in your past roles to drive project success.

Use this opportunity to showcase your problem-solving skills. Describe the challenge, your analysis of it, the solution you implemented, and the impact it had on the project. Tailor your story to demonstrate critical thinking and innovation.

Emphasize your communication skills and your efforts to understand the product team's objectives. Share examples of how you have collaborated on cross-functional projects, ensuring alignment and clear communication throughout the process.

Discuss any relevant projects where you've worked with AI or machine learning models, particularly how you integrated these models into data pipelines or how you dealt with model training and monitoring. Highlight your understanding of these technologies.

Share your strategies for professional development, such as attending industry conferences, participating in online courses, or following relevant publications. Convey your passion for continuous learning and staying ahead of industry trends.

Outline specific instances where you optimized data processing time or resource usage in your previous roles. Detail the techniques and methodologies you used to achieve efficiency gains and the tools that supported your initiatives.

Explain the tools and strategies you've implemented for monitoring the performance and reliability of data pipelines. Include your methods for identifying bottlenecks and ensuring the smooth operation of services.

Articulate your enthusiasm for Visa's commitment to innovation in the payments industry. Share how your skills align with the company's mission and how you see this position as a vital part of your career journey.