Data Engineer - job 2 of 9

As a Data Engineer at Visa, you will collaborate with cross-functional teams to design and deploy data pipelines, build data models and data warehouses, and facilitate Business Intelligence solutions. You’ll also be responsible for creating dashboards and reports using tools like Tableau and Power BI, while applying machine learning techniques to enhance our data-driven business solutions.

To qualify for the Data Engineer role at Visa, candidates should possess a Bachelor's or Master's degree in computer science or a related field, with 0.6-1.6 years of relevant work experience. Strong analytical skills, proficiency in programming languages like Python, and familiarity with technologies such as Hadoop, Spark, and AI-centric libraries are essential.

Data Engineers at Visa typically utilize a variety of tools and technologies including PySpark and SQL for data manipulation, Hadoop and Hive for data storage, and Tableau or Power BI for data visualization. Additionally, familiarity with machine learning libraries such as TensorFlow and Keras is beneficial.

The Data Engineer role at Visa is a hybrid position, meaning you will have the opportunity to work both remotely and in-office. The specific expectation for in-office days will be confirmed by your hiring manager.

At Visa, Data Engineers work within collaborative teams that include Data Analysts and Data Scientists. You will be involved in fostering a culture of accountability and innovation and will regularly engage with cross-functional partners to ensure that data solutions meet business needs effectively.

In your answer, highlight specific projects where you successfully built and deployed data pipelines. Discuss the technologies used, challenges faced, and how you overcame them, demonstrating your hands-on capability in data engineering.

Explain your approach to data validation and testing within your data pipelines. Provide examples of methodologies you've used in the past to maintain accuracy and reliability, such as using automated tests and data profiling techniques.

When answering this, share specific examples of reports or dashboards you've created, the insights derived from them, and how they helped stakeholders make informed decisions, emphasizing your ability to present complex data clearly.

Provide insights into how you've implemented machine learning models in projects. Mention any specific algorithms you've worked with, frameworks you've utilized, and the practical outcomes of your efforts, showcasing your expertise in this area.

Discuss the ways you keep up with trends, such as attending workshops, participating in online courses, or reviewing tech blogs and forums. Emphasize your commitment to continuous learning as a Data Engineer.

Use the STAR method (Situation, Task, Action, Result) to outline a specific challenge, your role in addressing it, the actions you took, and the successful outcomes that resulted from your solutions.

Explain your familiarity with Agile practices, highlighting your experiences working in Agile teams, and how it has improved project outcomes. Point out specific ceremonies or tools you’ve used, like Scrum, JIRA, or sprint planning.

Highlight your teamwork approach, emphasizing communication and flexibility in working with cross-functional teams. Provide examples of how you've effectively shared knowledge and worked towards common goals.

Detail how you've used Git for version control in your projects, emphasizing best practices such as branching, committing, and merging. Explain any particular experiences where Git helped enhance collaboration within your team.

In your response, reflect on Visa's mission and values and tailor your answer to show how they align with your career goals. Highlight what excites you about the role and the opportunity to contribute to Visa’s transformative work in payments technology.