Data Engineer - Sr. Consultant level- Core Data Assets - job 15 of 21

As a Data Engineer - Sr. Consultant level at Visa, your primary responsibilities include designing, coding, and testing data models, building and maintaining data pipelines, and implementing robust data validation processes. You will also be driving the development of innovative data solutions for automated scoring models and working on secure AI and data science model deployments that can handle large volumes of data. Collaboration with product delivery teams is essential, ensuring that you successfully implement proof of concepts and early products within Visa's ecosystem.

To qualify for the Data Engineer - Sr. Consultant level role at Visa, you should possess a strong background in data engineering, including proficiency in data modeling and building scalable data pipelines. Experience with machine learning models, data validation, and cleansing techniques is critical. A degree in Computer Science, Information Technology, or a related field is preferred, alongside hands-on experience with database structures and cloud platforms. Additionally, strong communication skills and the ability to present technical solutions to non-technical stakeholders are necessary.

The Data Engineer - Sr. Consultant level at Visa plays a transformative role in the digital payment industry by developing comprehensive data solutions that enable innovation within Visa’s core services. By designing efficient data pipelines and integrating AI into data operations, you ensure that Visa can offer high-quality, data-driven products and services that meet evolving customer needs. Your contributions will help streamline processes, enhance data accessibility, and ultimately lead to smarter financial services.

Success as a Data Engineer - Sr. Consultant level at Visa requires a diverse skill set, including advanced programming skills, strong knowledge of database management systems, and a solid understanding of data modeling. Familiarity with cloud technologies, machine learning frameworks, and data validation techniques is also essential. Furthermore, excellent analytical and problem-solving skills, along with effective communication abilities, will empower you to express complex concepts clearly to different audiences, ensuring successful collaboration across teams.

The Data Engineer - Sr. Consultant level position at Visa is a hybrid role, allowing you to split your time between remote work and the office. Employees are typically expected to work from the office 2-3 set days a week, which helps foster collaboration and team engagement. This flexible work arrangement supports a balanced approach to maximize productivity and maintain strong communication within teams.

Certainly! When answering this question, illustrate your experience with designing and implementing data models by discussing specific projects where you created conceptual, logical, and physical data structures. Highlight your understanding of ensuring data integrity and the tools or methodologies you used, along with the outcome of the project.

Explain your methodology for creating scalable data pipelines by discussing how you assess data requirements, select suitable technologies, and design workflows. Mention any tools you’ve used (like Apache Kafka, Spark, etc.) and emphasize the importance of monitoring and auditing processes to ensure data quality throughout.

In your response, define data validation and cleansing techniques you commonly implement, such as data profiling, anomaly detection, and normalization. Discuss examples where you successfully identified and resolved data quality issues and how this contributed positively to the overall data management process.

Share a specific project where you've integrated AI or data science solutions, detailing your role and the technologies employed. Discuss the challenges faced, how you tackled them, and the impact of the project on the business or customers. This illustrates your hands-on experience with advanced technologies relevant to the Data Engineer - Sr. Consultant level position.

Discuss your strategies for fostering collaboration, such as utilizing project management tools, regular team meetings, and open communication channels. Provide examples of platforms you’ve used to facilitate teamwork, and comment on how effective collaboration enhances project outcomes in data engineering.

Share your familiarity with various cloud platforms (like AWS, Google Cloud, Azure) and elaborate on specific projects where you utilized cloud services for data storage, processing, or analytics. Highlight the benefits these platforms provided, particularly concerning scalability, reliability, and performance in your data engineering tasks.

Emphasize your commitment to continuous learning. Discuss resources such as industry journals, online courses, webinars, or tech forums where you stay informed about emerging tools and trends. Tailor your response to how this knowledge helps you innovate and apply contemporary practices to your work at Visa.

Define success in a data engineering project by discussing key indicators such as meeting project deadlines, achieving desired outcomes, ensuring data quality, and satisfying stakeholder needs. Share a concrete example where you contributed to a successful project and the measures that lead to its success.

Reflect on specific challenges you've faced, such as data quality issues, scalability problems, or integration challenges. Outline your thought process and the steps you took to address these obstacles, ensuring to highlight the positive results that followed your solutions.

Articulate the importance of data governance in terms of data quality, security, and compliance. Discuss frameworks, policies, or tools you've applied to manage data responsibly and ensure that processes align with business objectives and regulatory requirements.