Sr. Data Engineer - job 13 of 29

As a Sr. Data Engineer at Visa Technology & Operations LLC, your primary responsibilities include performing data engineering activities on Hadoop and the Greenplum Data Warehouse (GPDB) ecosystem. You'll work closely with very large datasets, develop programs for Massively Parallel Processing (MPP) Data Warehouse platforms, and collaborate with your team to utilize Big Data technologies effectively.

To qualify for the Sr. Data Engineer position at Visa Technology & Operations LLC, candidates should possess substantial experience in data engineering, specifically with Hadoop and GPDB ecosystems. A strong background in Big Data technologies, programming skills, and the ability to handle data from disparate sources is essential. Additionally, familiarity with IT security requirements and compliance is highly beneficial.

The Sr. Data Engineer role at Visa Technology & Operations LLC plays a crucial part in enhancing IT security by managing long-term retention of security system logs and ensuring compliance with regulatory requirements. You’ll also be tasked with debugging applications and performance testing, which contribute to safeguarding the organization's data integrity.

Yes, Visa Technology & Operations LLC offers flexibility that allows for partial telecommuting for the Sr. Data Engineer role. This means you can balance your work between the office in Austin, TX, and your home, depending on your preferences and team needs.

In the role of Sr. Data Engineer at Visa Technology & Operations LLC, you will be using tools associated with Hadoop and the Greenplum Data Warehouse ecosystem. Familiarity with Big Data technologies will also be essential as you'll collaborate with your team to leverage these tools effectively in your projects.

In answering this question, highlight specific projects or tasks you've completed using Hadoop and Greenplum. Discuss your role, the challenges you faced, and the outcomes achieved, demonstrating your technical proficiency and problem-solving skills in data engineering.

To tackle large datasets, share your strategies for data processing, including the tools and methodologies you employ, such as Massively Parallel Processing (MPP). Convey how you prioritize efficiency and accuracy while managing data loads and transformations.

Discuss your systematic approach to debugging, emphasizing the importance of identifying root causes, leveraging logs, and making use of performance testing tools. Provide examples of past experiences where you successfully debugged applications.

Choose a project that showcases your skills as a Sr. Data Engineer. Describe the obstacles you faced, how you approached solving them, and the successful results achieved. A focus on collaboration with team members can also highlight your teamwork abilities.

Mention specific resources, such as online courses, industry blogs, webinars, or conferences, that you engage with to stay informed. Highlighting any communities or networking you partake in can show your commitment to professional growth.

Illustrate how a Sr. Data Engineer is integral to IT security by ensuring data handling practices comply with security protocols and regulatory requirements. Discuss the importance of data integrity and the long-term retention of security logs.

Outline your systematic approach, starting with data assessment from each source, followed by transformation processes, and ending with load strategies. Emphasize the need for data quality checks and collaboration with data owners.

Share your practices for performance testing, such as creating benchmarks, monitoring resource usage, or using specific tools. Discuss the importance of iterative testing and responsiveness to results for optimizing performance.

Explain how you prepare for meetings by gathering relevant data insights and updates. Emphasize your collaborative mindset, willingness to provide input, and how you actively contribute to discussing team challenges and project goals.

Mention programming languages such as Python, Java, or SQL that are crucial for data engineering tasks. Discuss how you use these languages in specific contexts, providing insight into your coding proficiency and data manipulation skills.