SW Engineer (Testing in Data Engineering)

As a SW Engineer in Testing in Data Engineering at Visa, your key responsibilities will encompass developing and testing automation frameworks, contributing to core product code, and ensuring the timely delivery of high-quality products. You'll also engage in design, development, and release deployments while providing post-deployment support. Communication is vital, as you'll regularly update your team on project statuses and potential risks.

To be a strong candidate for the SW Engineer position at Visa, it’s essential to have a Bachelor’s degree or equivalent experience along with at least 3 years of relevant work experience. A solid foundation in software development, especially in testing data-centric projects, is important. Skills in Java, Big Data technologies like Hadoop, and a good understanding of data structures are also crucial for this role.

For the SW Engineer position at Visa, proficiency in Java is essential. Additionally, familiarity with Big Data technologies such as Hadoop and Spark, Unix/Linux operating systems, Shell scripting, and RDBMS, along with SQL and in-memory databases like Redis, will significantly benefit your application. Experience in working with version control systems like Git is also preferred.

Visa is committed to professional growth for its SW Engineers through initiatives such as ongoing training programs, participation in industry conferences, and access to advanced tools and technologies. You the opportunity to engage in AI/ML development projects, further enhancing your skills in line with industry trends while working collaboratively within a dynamic team environment.

The work environment for SW Engineers at Visa in Singapore is dynamic and collaborative, fostering innovation and creativity. The hybrid setup allows for flexible work arrangements, empowering you to find a balance that suits your personal and professional needs. With a strong focus on teamwork and open communication, Visa cultivates an inclusive atmosphere where contributions from diverse backgrounds are valued.

When addressing this question, highlight a specific project that presented unique challenges in testing automation frameworks or data-centric projects. Discuss your role, the methods you employed to tackle challenges, your contributions to the project’s success, and the lessons learned from that experience.

Be prepared to discuss your hands-on experience with automation frameworks. Include specifics about the frameworks you’ve used, how you’ve implemented them in past projects, and any metrics or improvements in efficiency you achieved through automation.

Share your approach to identifying risks in project scopes. Discuss tools and methods you have used, how you engage team members in the process, and any frameworks you follow to mitigate identified risks effectively.

Discuss your experience working within Agile frameworks, including specific methodologies such as Scrum or Kanban. Explain how Agile practices have improved collaboration, communication, and delivery effectiveness in your previous roles.

Explain the steps you take to guarantee quality software. This can include writing comprehensive test cases, employing automation, conducting code reviews, and collaborating closely with the development team to address bugs before deployment.

Talk about your communication style and how you initiate status updates, discussions about issues, and risk assessments. Emphasize the importance of transparency and regular check-ins within your team to foster a collaborative environment.

Discuss your understanding of data governance and its significance in ensuring data quality, privacy, and compliance within software projects. Share how you’ve applied data governance principles in past work and the impact on project outcomes.

Provide a relevant example where you effectively utilized data structures to solve a complex problem. Explain the challenge, your thought process in selecting the appropriate data structures, and how your solution impacted the project.

Share the resources you use, such as blogs, webinars, online courses, or conferences that you attend. Discuss any projects where you've implemented the knowledge gained from self-education into your work, showing your commitment to continuous learning.

Talk about your experience with Big Data technologies like Hadoop or Spark, focusing on specific projects where you've tested these systems. Highlight your understanding of their intricacies and the tools you utilized to ensure performance and reliability.