Staff Data Engineer - job 0 of 50

The Staff Data Engineer at Visa Technology & Operations LLC is responsible for creating new capabilities for the AI Platform, refactoring existing functionalities for improved performance and maintainability, and driving the end-to-end development of data-driven business solutions. You will also work with a variety of project team members to ensure that solutions meet requirements and adhere to our architectural vision.

To qualify for the Staff Data Engineer position at Visa Technology & Operations LLC, candidates typically need strong programming skills, deep knowledge of data engineering practices, and experience with performance optimization techniques. A background in software development and familiarization with AI platforms are also highly beneficial.

Collaboration is essential for a Staff Data Engineer at Visa Technology & Operations LLC as you will work closely with Product Managers, Architects, Analysts, and Software Engineers. This teamwork ensures that all data-driven solutions are developed efficiently and meet the project’s objectives while aligning with the company's standards.

Absolutely! The Staff Data Engineer position at Visa Technology & Operations LLC provides ample opportunities for professional growth and career advancement. As part of a leading company in the financial technology space, you will gain exposure to innovative projects and technologies that can help further your career.

At Visa Technology & Operations LLC, Staff Data Engineers enjoy a healthy work-life balance. The role offers the flexibility of partial telecommuting, allowing you to manage your work responsibilities while still having time for personal life. The company values employee well-being and promotes a supportive work environment.

In answering this question, highlight specific projects where you implemented data engineering techniques, discuss the technologies you used, and explain how you ensured data quality and integrity. Show your understanding of data pipelines and how they play a role in business solutions.

Talk about your strategies for task management, such as using project management tools or methodologies like Agile. It's important to emphasize your ability to adjust priorities based on team needs and project deadlines, showcasing relevant examples from previous work.

Provide a detailed account of a specific situation where you refactored code, explaining the initial challenge, the steps you took to modify the code, and how these changes ultimately improved performance. Demonstrating your problem-solving skills and technical expertise is key.

Outline your approach, starting with requirement gathering, then discuss your design considerations, potential risks, and your method for cross-functional collaboration. It's crucial to articulate your process and problem-solving methodology clearly.

This is an opportunity to showcase your foresight and understanding of the common challenges in data engineering. Discuss potential pitfalls, such as data silos or scalability issues, and how you would address these through effective communication, planning, and technology choices.

Mention industry conferences, webinars, blogs, or communities you follow to remain informed about trends and technologies. Emphasizing your commitment to continuous learning and how this knowledge can benefit Visa Technology & Operations LLC will resonate well.

Provide an example that demonstrates your ability to simplify complex technical concepts. Highlight your communication style, adaptability, and the importance of clear communication in facilitating collaboration within teams.

Discuss specific tools or technologies you have experience with, such as SQL, Apache Spark, or ETL tools. Explain why you prefer these tools and how they contribute to effective workflow and solutions in data engineering.

Talk about best practices for data security, such as encryption, access controls, and compliance with regulations like GDPR. Highlight your proactive approach to incorporating security measures into the development process.

Discuss the importance of stakeholder feedback and how you actively seek it throughout the project lifecycle. Explain how you use their insights to improve data solutions and ensure alignment with business objectives.