Sr. Data Engineer - job 5 of 29

As a Sr. Data Engineer at Visa Technology & Operations LLC, your main responsibilities include performing data engineering activities within the Hadoop and Greenplum Data Warehouse ecosystems. You’ll work with large data sets and develop programs utilizing Massively Parallel Processing (MPP) Data Warehouse platforms. Other key tasks involve loading data from various sources, ensuring proper documentation, conducting performance testing, debugging applications, and adapting to IT security standards to handle data retention effectively.

To be considered for the Sr. Data Engineer position at Visa Technology & Operations LLC, candidates typically need a degree in Computer Science, Engineering, or a related field, along with extensive experience in data engineering, particularly with Hadoop and Greenplum Data Warehouse technologies. Proficiency in handling large data sets and familiarity with Big Data tools are crucial. Additionally, a strong understanding of IT security requirements and regulatory compliance will significantly enhance your application.

Visa Technology & Operations LLC promotes collaboration among data engineering teams by encouraging a culture of idea-sharing and teamwork. As a Sr. Data Engineer, you will engage in collaborative projects, contribute to discussions in team meetings, and work closely with colleagues to solve complex problems. This environment fosters innovation and knowledge sharing, ensuring that all team members can leverage each other's expertise effectively.

As a Sr. Data Engineer at Visa Technology & Operations LLC, you will work with a variety of Big Data technologies, including Hadoop and Greenplum Data Warehouse systems. You may also encounter tools and frameworks for data processing and storage, such as Spark, Hive, and various data ingestion methods that enable you to manage and analyze large data sets efficiently.

Yes, the Sr. Data Engineer position at Visa Technology & Operations LLC does allow for partial telecommuting. While the role primarily requires presence at the Austin, TX office, the company understands the importance of flexibility and supports a balanced work-life dynamic, enabling employees to work remotely part of the time.

To answer this question, highlight your hands-on experience with Hadoop and Greenplum, focusing on specific projects where you've utilized these technologies. Discuss the types of data sets you've worked with and the outcomes of your efforts, demonstrating your technical expertise and how you overcame challenges.

When responding, outline the steps you took to design and implement the data pipeline, including the technologies used, the data sources you integrated, and how you ensured reliability and performance. Emphasize your problem-solving skills and how the flow of data resulted in valuable insights.

Explain your systematic approach to debugging, including how you identify issues, analyze data flows, and utilize performance testing tools. Share an example where your debugging efforts significantly improved application performance or resolved a critical issue.

Discuss your understanding of IT security requirements and the steps you take to ensure compliance, such as encryption practices, data retention policies, and regular audits. Mention any specific frameworks or standards you're familiar with that guide your work in maintaining security.

Share your methods for keeping current, such as following industry blogs, attending conferences, participating in webinars, and leveraging online courses. Convey your passion for continuous learning in the field of Big Data and data engineering.

Use the STAR method (Situation, Task, Action, Result) to describe the project, focusing on your role in collaboration. Highlight your communication skills and how your contributions helped the team achieve its goals.

Discuss your experience with performance testing techniques, tools you've used, and how you interpreted results to optimize data workflows. Provide examples where your testing led to significant performance improvements.

Illustrate your time management skills by detailing your prioritization process. Mention any tools or techniques you use to stay organized and responsive to changing project needs in a team environment.

Share specific challenges related to managing large data sets, such as scalability or processing speed, along with your problem-solving strategies. Highlight successful outcomes as a result of your efforts.

Explain the importance of documentation, your preferred practices for maintaining clear and thorough records, and how this benefits both the team and project continuity. Highlight any tools or systems you prefer to use for documentation.