How to ace data visualization interviews at FAANG companies
By: Bao Nguyen
Tags: Interview Tips, Data Analyst, Data Visualization

Photo by Tim Gouw on Unsplash

When it comes to technical interviews, we all think about SQL, coding, or statistics interviews. However, there is one area that is also important, which is data visualization. This article is about how to ace data visualization interviews.

A few months ago I was selected to the final round for a Business Analyst role at a FAANG company. There were four interviews, including two behavioral, one data visualization, and one data analytics. Although I didn’t get the job eventually, my recruiter said that their feedback on my data visualization interview was very positive. Therefore, I guess I earned a “pass” at least in that interview. I want to share with you how I aced the data visualization interview in this article.

The data visualization interview lasted in 45 minutes. The team wanted to evaluate the candidate’s ability to design effective visualizations and learn about their experiences designing various types of visualizations. Here are the questions that I received and my approach to those questions.

Photo by William Iven on Unsplash

What is your data visualization philosophy?

I bet all of you will agree with me that this is a very broad question. Everyone can come up with a different answer. My data visualization philosophy is that my visualizations need to tailor to the target audience’s needs as much as possible. A dashboard is useless when no one looks at it.

I made sure that I defined clearly the target audience. I worked with them closely to understand their needs regarding metrics and types of visualization. I closely followed up with them to promptly any change in their need.

Tell me about a data visualization project that you were very proud of?

This question is the most expected question before the interview, so I already prepared two to three stories and practiced very carefully. For each story, the STAR method (Situation — Task — Action — Result) always works. I talked about a very specific situation when I had to build a dashboard. I described the purpose of the dashboard, the key stakeholders a.k.a. target audience, how I worked with the stakeholders to come up with the metrics, and what types of visualizations I made.

I also shared about a time when the initial plan didn’t work out as expected, when there was a change in stakeholders’ needs, and how I followed up with the stakeholders to ensure the dashboard works in the way that they expected. I summarized my story by sharing the key learning points that I got after that experience.

What data visualization tools that you use?

I use Tableau as the main tool of data visualization during my past roles, so Tableau is a no-brainer answer for me. I described what advanced Tableau functions or features that I used. The main point is to talk about a data visualization tool that you are good at, not to list a lot of tools that you learn or know about.

However, Tableau (or other similar data visualization software) is not the only way to visualize data. Drawing a chart using Google Sheets works too! It depends on the target audience and the purpose of visualizing data. For example, I use a simple Google Sheets chart when I need a quick way to visualize the data set, when my data set needs to be shared across a group of users or when my stakeholder is a non-technical data user.

A data visualization case study

The question is: “Suppose our company has a few offices around the US. We want to know the performances of those offices to optimize the space for our employees. Your job is to build a dashboard to show office utilization performance”.

I received a preview of the data sets. I had to build an imaginary dashboard using Google Drawings. You can draw charts in Google Drawings using a similar approach when drawing charts in Google Sheets.

Before jumping in the visualizing steps, I asked the interviewer who are this dashboard for. The dashboard is for executive-level managers. To me, that means I need to show the highest-level metrics so that the managers know what is going on by looking at this snapshot. Then, I brainstormed the metrics to show. I came up with three to four metrics.

I didn’t only build the charts and graphs. For each metric, I explained the rationale behind using this type of visualization and not the other. Talking out loud the process not only helps show the thought process but also makes me realize that some other types of charts express my metric better compared with the chart that I came up within the first place. Also, charts and graphs aren’t only pie charts, bar graphs, or line graphs. You can use typography, which means showing the pure key numbers in this case. The dashboard users can get the important figures immediately without having to find from the charts or graphs.

A dashboard is not enough without the filters. I spent time thinking about appropriate filters, drawing those, and explaining to the interviewer. Some important filters include date range, locations/ markets, and time-frequency (where users can select a daily, weekly, or monthly view).

After all, I summarized the key points about my dashboard, including the target audience, important metrics, types of visualizations, and filters. I also mentioned a potential way to further develop the dashboard in the future if have more variables in the data set or more stakeholders involved.

Conclusion

My interview experience is unique and by no means would be the same for everyone. It serves as a single data point and should not be generalized to all data visualization interviews. I hope you gained some insights and perspectives from my experience to help you tailor your interview preparation and to ace data visualization interviews.