Sr. Data Engineer - job 8 of 29

As a Sr. Data Engineer at Visa Technology & Operations LLC, you will be responsible for performing data engineering activities within the Hadoop and Greenplum Data Warehouse ecosystems. This includes handling large datasets, ensuring efficient data loading from disparate sources, debugging applications, and participating in project meetings to represent the team. Additionally, you will address regulatory compliance and IT security requirements while collaborating closely with your peers.

To qualify for the Sr. Data Engineer role at Visa Technology & Operations LLC, candidates typically need a solid background in data engineering, particularly with Hadoop and Greenplum Data warehouses. Familiarity with Big Data technologies, Massively Parallel Processing (MPP) platforms, and experience with security-related data management are also essential. A degree in Computer Science, Engineering, or a related field is usually preferred.

As a Sr. Data Engineer at Visa Technology & Operations LLC, you will work primarily with Hadoop and Greenplum Data Warehouse systems, alongside a variety of Big Data tools and technologies designed for data processing and analysis. You'll also encounter technologies that support security logging and compliance measures addressing the dynamic nature of IT security challenges.

Yes, the Sr. Data Engineer position at Visa Technology & Operations LLC allows for some flexibility with partial telecommuting. This blends the benefits of in-office collaboration in our Austin, TX location with the ability to work remotely, giving you the best of both worlds.

To prepare for your interview for the Sr. Data Engineer position at Visa Technology & Operations LLC, focus on your experience with Hadoop and Greenplum ecosystems, as well as any Big Data technologies you have used. Be ready to discuss problem-solving approaches to performance testing and debugging issues, and ensure you understand the implications of regulatory compliance in data management.

When answering this question, detail any specific projects you've worked on, your role, the challenges you faced, and how you overcame them. Discuss the scale of the datasets you've managed and any performance optimizations you've implemented.

Highlight your systematic approach to debugging, mentioning tools and methodologies you use. Provide examples of complex problems you have solved in the past and the impact of your solutions.

Discuss your understanding of regulatory requirements relevant to data engineering and describe the protocols you follow to ensure data security, including any experience with security log management and compliance adherence.

Emphasize the performance testing frameworks and tools you are familiar with. Provide specific examples where you have identified performance bottlenecks and implemented solutions that significantly improved data processing times.

Share a specific instance emphasizing your collaborative skills. Highlight your role, your contributions, any challenges the team faced, and the successful outcome achieved through teamwork.

Provide detailed examples of projects where you implemented MPP techniques. Discuss the volume of data processed, the technologies used, and the overall impact on business outcomes.

Discuss the resources you use to stay updated on industry trends such as blogs, online courses, webinars, or tech conferences. Share specific technologies you're currently exploring.

List the Big Data tools you are comfortable using, such as Apache Spark, Kafka, or others, and explain how you've applied them effectively in your data engineering projects.

Describe your methodology for task prioritization, such as using project management tools or Agile methodologies. Illustrate your answer with a real-world example to show how you effectively managed competing deadlines.

Share your passion for data engineering, mentioning aspects such as problem-solving, innovative technology application, or collaboration. Make the answer personal and relatable to engage the interviewer.