Data driven interviewing with Tableau


Hi

Continuing the series of posts where I explain how we are building an enterprise grade Tableau Centre of Excellence.

Here at Vizninja towers we pride ourselves on knowing Tableau & data. After all, we need to be able to add value and help users with their myriad queries.

So when we get the chance to hire, it is critical that we get the correct people. People with great skills in Tableau, data & visual analytics. People that can tell stories and make data come to life. People who want to help others see and understand their data. And being a data driven team we use data and visualisation to help us make the selection.

Our interview process goes like this.

  1. An initial screening call with the Agile BI service manager (that’s me!)
  2. A technical interview with the team
  3. An exercise involving Tableau Public
  4. A final chat with the big boss (that’ll be me one day)

Some more detail on a couple of these steps.

 

The Technical Interview

We have a series of technical questions that the team asks each candidate. The questions are split between Tableau Server and Tableau Desktop and also categorised in terms of complexity – e.g. Level 1, Level 2 & Level 3, (see here) with the more complex questions being at L3 level. So I wait until my team are in a bad mood and then I let them off their leash at the candidate….

Click the image to get a better view of the tooltips. Apologies if they’re not so clear. Here’s what some of them look like. So we can see the exact question asked, points achieved and any comments.

On the dashboard, you can see the questions asked, the max points available per question and then the points attained per category and complexity. At the end we spit out a KPI that gives us some indication of a candidate’s capability. Note that a low score doesn’t necessarily indicate that a candidate is unsuitable. Often we see people who are super-skilled in Tableau Desktop but not experienced in Server (as in this case). A few weeks with the team will soon change that though. Our job is to create all-rounders in all aspects of Tableau.

So if the data checks out then the candidate moves on to the next stage.

 

The Tableau Public Exercise

For the next test we ask a candidate to choose a dataset from these public datasets and then create a viz on Tableau Public. The candidate then presents their viz to us and we look for the following

  • Good visual analytics best practice
  • Ability to create an engaging story and develop insight
  • Structured design process and ability to justify design choices

And if they’re really unlucky then @jakesviz will download the workbook and rip it to bits in front of them! Yes we are looking to see if you’ve commented your calculated fields!

Here’s what Jakub Jaros came up with..

https://public.tableau.com/profile/jakub.jaros#!/vizhome/SignigicantVolcanicEruptions/Main

Nice work huh? We thought so. So now you know where to go for your volcano information. This is a really important part of the interview process as the candidate presents their work to us and it can lead to discussion, debate and even argument. But it really gives a sense of whether someone loves dataviz and you sure need that if you want to work for me. We plan to add some data points to this stage so that we can come up with a final rating for each candidate.

After this, it’s a final chat with the big boss and hopefully a role with the team. And that’s when the fun really starts!

This approach has really resonated with senior management and as a result we are helping several other teams to adopt a similar process.

So there you are. That’s how we ensure we have the correct people to deliver a great service. Feedback appreciated in the comments.

Cheers, Paul

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