Sr. Data Engineer - job 15 of 29

As a Sr. Data Engineer at Visa Technology & Operations LLC, you'll dive into activities involving the Hadoop and Greenplum Data Warehouse ecosystems. Your responsibilities will include handling large data sets, developing programs that take advantage of MPP Data Warehouse platforms, and utilizing Big Data technologies with a focus on collaboration and sharing ideas with your team.

To qualify for the Sr. Data Engineer position at Visa Technology & Operations LLC, applicants should have significant experience in data engineering, particularly with tools like Hadoop and Greenplum. A solid understanding of performance testing, debugging applications, and IT security compliance is also crucial. Strong skills in handling large data sets and collaborative problem-solving are essential.

Sr. Data Engineers at Visa Technology & Operations LLC leverage a variety of Big Data technologies and tools, particularly Hadoop and the Greenplum Data Warehouse architecture. They work with Massively Parallel Processing for data handling, ensuring they can effectively manage and analyze large volumes of data to meet their project goals.

Yes, the Sr. Data Engineer position at Visa Technology & Operations LLC allows for partial telecommuting. While the role is based in Austin, TX, the company supports flexible work arrangements to balance in-office collaboration and personal work preferences.

Visa Technology & Operations LLC prioritizes data security, which is an integral part of the Sr. Data Engineer role. Responsibilities include addressing the evolving threat landscape and maintaining regulatory compliance by managing long-term retention of security system logs and sensor logs, ensuring a high standard of security is upheld.

When answering this question, focus on specific projects where you've utilized these technologies, detailing your role and the impact your work had. Highlight any challenges you faced and how you overcame them.

Discuss various methodologies you implement for performance testing, such as load testing and stress testing. Providing examples of past experiences where these strategies improved system performance will add credibility.

Mention specific resources you utilize, such as industry blogs, online courses, or community forums. Sharing personal anecdotes about how you've adapted your skills or workflows in response to new technologies will demonstrate your commitment to continuous learning.

Employ the STAR method (Situation, Task, Action, Result) to structure your answer. Describe the complexity of the issue, the steps you took to resolve it, and the eventual outcome, emphasizing teamwork if applicable.

Explain your prioritization methods, possibly touching on frameworks like agile or sprint planning. Illustrate your answer with examples from past experiences to show how you managed multiple projects effectively.

Discuss the specific tools you've used (like Apache Spark, SQL, Python Pandas) and elaborate on why you prefer them, including factors such as ease of use, efficiency, and compatibility with existing systems.

Focus on your communication strategies and collaborative tools you use (e.g., Jira, Confluence). Give an example of a successful project that involved multiple team members, highlighting your role in facilitating collaboration.

Provide a detailed narrative around how you addressed security protocols while still achieving project goals. Discuss the balance between ensuring data security and efficiently executing engineering tasks.

Talk about your understanding of data retention policies and compliance regulations. Share specific best practices you follow, perhaps including tools or methods to document and maintain data appropriately.

Use analogies or simple language to clarify MPP Data Warehousing. Emphasize its advantages, such as scalability and performance for complex data processing tasks, communicating its significance to business operations.