Sr. Data Engineer - job 22 of 29

As a Sr. Data Engineer at Visa Technology & Operations LLC in Austin, your key responsibilities include performing data engineering tasks on the Hadoop and Greenplum Data warehouse ecosystems. You'll be working with large datasets and development of applications that utilize Massively Parallel Processing (MPP). Additionally, your role will include loading data from various sources, documentation, performance testing, and responding to compliance and security requirements.

To excel as a Sr. Data Engineer at Visa Technology & Operations LLC, candidates typically need a background in computer science or a related field, with several years of experience in data engineering roles. Proficiency in Big Data technologies, Hadoop, and experience with the Greenplum Data Warehouse is crucial. Excellent analytical skills, problem-solving abilities, and experience in handling large datasets are also essential qualifications.

At Visa Technology & Operations LLC, you can expect to join a collaborative and innovative team environment. As a Sr. Data Engineer, you will work closely with other data professionals, sharing ideas and strategies to leverage Big Data technologies effectively. The company fosters a culture of teamwork, where professionals are encouraged to contribute and implement their best ideas to advance data projects.

In the Sr. Data Engineer role at Visa Technology & Operations LLC, you will predominantly work with Hadoop and Greenplum Data warehouse (GPDB) ecosystems. Additionally, you will utilize various Big Data tools and technologies, focusing on Massively Parallel Processing (MPP) systems to build and optimize applications dealing with large datasets.

Yes, the Sr. Data Engineer role at Visa Technology & Operations LLC in Austin offers flexibility, including the possibility for partial telecommuting. This allows you to maintain a healthy work-life balance while contributing to exciting and innovative data projects.

In responding to this question, highlight your hands-on experience with Hadoop. Discuss specific projects where you've utilized Hadoop for data storage and processing, emphasizing your role in optimizing data pipelines and handling large datasets effectively.

Share techniques you've implemented to optimize data processes, such as indexing, partitioning, and leveraging MPP technologies. Pointing to relevant metrics or outcomes from past experiences can strengthen your answer.

Explain your approach to data validation and cleaning processes. Discuss any specific tools or frameworks you've used to maintain data quality and the importance of documenting these processes to support data integrity.

Take the opportunity to illustrate your problem-solving skills. Provide specific examples of challenges faced in previous roles and detail the steps taken to analyze and resolve these issues, including any technologies or methodologies applied.

Discuss your familiarity with Greenplum, touching on specific projects wherein you utilized the platform to transform data for analysis. Mention any particular features that you find beneficial for data engineering tasks.

Talk about your understanding of data compliance standards, and describe the measures you've taken to ensure security in data handling, including how you've adapted processes to meet regulatory requirements.

Focus on your experience collaborating with cross-functional teams. Share examples of how you've contributed to team success while promoting open communication and sharing innovative ideas in data projects.

Illustrate your commitment to professional growth by mentioning relevant blogs, courses, or conferences you follow to keep pace with data engineering advancements. Discuss how you’ve applied new knowledge to enhance your work.

Clarify the concept of Massively Parallel Processing (MPP) and its advantages in handling large-scale data processing tasks. Emphasize real-world applications where MPP has dramatically improved performance in data engineering tasks.

Highlight critical skills such as proficiency in Big Data tools, analytical thinking, problem-solving abilities, and collaboration skills. Explain why these are crucial for the success of a Sr. Data Engineer, ensuring to reference how these skills contribute to effective data management and transformation.