Data Engineer - Sr. Consultant level - job 18 of 19

The Data Engineer - Sr. Consultant at Visa Technology & Operations LLC is responsible for designing and enhancing fraud detection solutions, shaping business problems into technical problems, overseeing development efforts, collaborating with cross-functional teams, and ensuring high-quality solutions are delivered on time. This role also entails mentoring juniors, developing data engineering processes, and executing projects both individually and in teams.

To qualify for the Data Engineer - Sr. Consultant position at Visa Technology & Operations LLC, candidates typically need a strong background in data engineering, proficiency in relevant programming languages, experience with data modeling and analytics, and excellent communication skills for collaboration with stakeholders. Prior experience in agile development environments and mentoring junior staff is also advantageous.

In the role of Data Engineer - Sr. Consultant at Visa Technology & Operations LLC, you will play a crucial part in designing and building advanced fraud detection solutions. This entails formulating complex data problems, ensuring alignment with business goals, collaborating with technical teams, and providing insights based on metric analyses to enhance detection capabilities.

As a Data Engineer - Sr. Consultant at Visa Technology & Operations LLC, you'll likely work with a variety of tools and technologies, including data modeling tools, programming languages such as Python or Java, big data frameworks, cloud platforms for data storage, and analytics tools. Familiarity with data governance frameworks and self-service data tools will also be beneficial.

The project delivery approach for a Data Engineer - Sr. Consultant at Visa Technology & Operations LLC emphasizes end-to-end management of development cycles, collaborating closely with various stakeholders, maintaining focus on timelines and budgets, while employing agile methodologies to ensure solutions are delivered efficiently and effectively.

When answering this question, you can share specific projects you've worked on, how you adapted to iterative development cycles, and any tools or methodologies you employed to ensure timely delivery of quality solutions. Highlight how collaboration with cross-functional teams was vital in these environments.

It's important to explain your process for breaking down business challenges into technical requirements. Discuss the strategies you employ for gathering inputs from stakeholders and how you ensure that the technical solutions meet business goals.

You might want to mention your approach to mentoring that includes hands-on training, facilitating knowledge sharing sessions, and encouraging a collaborative environment. Sharing success stories of how you’ve helped juniors grow can enhance your answer.

Here, discuss the mechanisms you put in place for code reviews, testing protocols, and your experience working with architects to maintain architectural integrity. Highlight how these practices not only ensure quality but also keep projects aligned with long-term goals.

You should elaborate on your ability to simplify complex technical concepts into relatable business terms. Discuss your techniques for presentations, regular updates, and tailored communication strategies that resonate with business stakeholders.

When addressing this question, provide a specific instance where you successfully juggled competing timelines and demands. Describe your prioritization strategies, how you communicated status updates, and maintained the quality of your work.

Explain the self-service data tools or analytics solutions you've developed. Highlight any specific technologies or frameworks you used and how they helped improve data accessibility and usability for other teams or business users.

Your response should include your approach to defining project scope, gathering requirements, and your experience in building data models that align with analytics needs. Discuss how you verify that attributes meet business requirements.

It's beneficial to talk about metrics you track for assessing project performance, including SLAs, data quality indicators, and usage statistics. Share your experience in defining and analyzing these metrics for various projects.

Here, tell a story about a specific instance where you identified a bottleneck and proposed an automated solution. Explain its impact on efficiency and how you went about implementing this change.