Staff Data Engineer - job 0 of 50

As a Staff Data Engineer at Visa Technology & Operations LLC, you will be responsible for developing new capabilities for our AI platform, refining existing code for better performance, collaborating with diverse project teams, and driving the development of data-driven business solutions. Your role includes overseeing the end-to-end development process, identifying risks, and presenting technical solutions in business-friendly terms.

To qualify for the Staff Data Engineer role at Visa Technology & Operations LLC, candidates typically require a mix of advanced technical expertise in data engineering, proficiency with programming languages, and substantial experience with databases and cloud services. Strong communication skills and a collaborative mindset are also essential for successfully working within diverse teams.

Yes, the Staff Data Engineer position at Visa Technology & Operations LLC is based in Austin, Texas, and may include partial telecommuting options, providing flexibility while allowing you to engage actively with your team on-site.

A Staff Data Engineer at Visa Technology & Operations LLC should possess strong programming skills, extensive experience with data modeling and database technology, and familiarity with big data frameworks. Skills in performance tuning, cloud platforms, and a good understanding of AI capabilities would significantly enhance your applications.

The work culture at Visa Technology & Operations LLC promotes collaboration, innovation, and continuous improvement. As a Staff Data Engineer, you'll work alongside skilled professionals in a supportive environment that values creative problem-solving and effective communication, allowing for personal and professional growth.

When answering this question, be specific about the tools you've used, such as databases, ETL tools, and cloud platforms. Mention how these tools helped in previous projects and demonstrate your ability to adapt to new technologies.

Choose a project where you faced significant challenges. Discuss the problem, the actions you took to resolve it, and the successful outcome. Highlight your analytical skills and teamwork in overcoming difficulties.

Talk about the testing techniques you apply, monitoring tools you use, and practices like code reviews and performance optimization that you implement to maintain high-quality data pipelines.

Explain your systematic approach to identifying, analyzing, and resolving data discrepancies. Emphasize your attention to detail and the importance of collaboration when resolving such issues.

Discuss the resources you use, like industry blogs, webinars, and professional networks. Mention that you’re proactive about learning new skills to remain competitive in the field.

Highlight the importance of communication and flexibility in cross-functional projects. Provide examples of successful collaborations and how you navigated any challenges that arose.

Detail the cloud platforms you’ve used (like AWS, Azure, or Google Cloud) and how they have played a role in your data engineering projects. Include specific examples of how you leveraged these technologies for efficiency.

Discuss the importance of code reviews in ensuring quality. Describe how you approach reviewing peers' code and how constructive feedback is part of the collaborative process.

Mention key performance indicators such as data throughput, latency, and error rates. Explain how analyzing these metrics helps in optimizing data solutions.

Provide insight into your project management strategies. Discuss tools you use for tracking progress and how you prioritize tasks to meet working deadlines while maintaining quality.