Staff Data Engineer - job 11 of 50

A Staff Data Engineer at Visa Technology & Operations LLC is tasked with creating new AI Platform capabilities, refactoring existing functionalities, and ensuring the development of data-driven solutions. This involves collaborating with various project team members, driving development efforts from initiation through delivery, and actively managing risks and issues throughout the solution development phases.

To thrive as a Staff Data Engineer at Visa, candidates should possess robust skills in data engineering, software development, and performance optimization. Familiarity with AI platforms, strong collaboration abilities, and excellent communication skills are also crucial to convey technical concepts to business stakeholders effectively.

Staff Data Engineers at Visa Technology & Operations work on projects that enhance the AI Platform capabilities. This includes designing and implementing code to handle new requirements, optimizing existing functionalities, and collaborating on innovative, data-driven business solutions to meet current industry challenges.

Yes, the Staff Data Engineer position at Visa offers the flexibility of partial telecommuting. While the role primarily reports to the Austin office, the company recognizes the importance of work-life balance and supports remote work options.

Visa Technology & Operations LLC provides extensive growth opportunities for Staff Data Engineers. With exposure to various projects across different phases of solution development, employees can enhance their technical skills, collaborate with senior staff, and potentially move into leadership roles focused on innovation and strategy.

When answering this question, discuss specific projects you've worked on that involved AI solutions. Highlight the technologies you used, your role in the project, and the outcomes. Be sure to mention any challenges you faced and how you overcame them to showcase your problem-solving skills.

Discuss your methodology for code refactoring, including understanding existing code architecture, identifying bottlenecks, and applying best practices in software development. Explain how you measure performance improvements to ensure the refactor adds value.

To answer this, detail your project management strategies, such as setting clear milestones, utilizing Agile methodologies, and fostering strong communication within the team. Give examples of how you've successfully delivered projects on time in the past.

Illustrate your experience by providing examples where you worked with Product Managers, Architects, and Analysts. Emphasize the importance of collaboration and how it facilitated successful project outcomes.

Share a specific instance where you had to present a technical concept to non-technical stakeholders. Explain how you simplified the language and focused on business outcomes to ensure your audience understood the value of your solutions.

Be prepared to discuss the specific programming languages, libraries, and tools you've used. Mention how these technologies have helped you achieve project goals and your readiness to learn new tools as needed.

Provide a situation where you noticed potential risks and took proactive measures to address them. Explain your steps and the results, demonstrating your ability to foresee challenges and act accordingly.

Share how you keep abreast of developments in the data engineering field—through online courses, attending workshops, following industry news, or participating in relevant communities. Highlight your passion for continuous learning.

Discuss qualities such as strong analytical skills, attention to detail, effective communication, and collaboration. Explain why you believe these traits are essential for success in a technical role.

Share your approach to managing changes in project requirements, emphasizing flexibility, communication with stakeholders, and the ability to adapt plans while keeping the team's objectives in mind.