{"id":8084,"date":"2022-06-30T09:19:19","date_gmt":"2022-06-30T16:19:19","guid":{"rendered":"https:\/\/coderpad.io\/?p=8084"},"modified":"2023-06-05T14:24:25","modified_gmt":"2023-06-05T21:24:25","slug":"building-a-better-future-for-data-teams-with-live-technical-interviews","status":"publish","type":"post","link":"https:\/\/coderpad.io\/blog\/interviewing\/building-a-better-future-for-data-teams-with-live-technical-interviews\/","title":{"rendered":"Building a Better Future for Data Teams with Live Technical Interviews"},"content":{"rendered":"\n

How should data teams work smarter in the future \u2014 and can better technical interviews help them do it? <\/p>\n\n\n\n

These were just some of the many thought-provoking questions I recently talked through with Boris Jabes of Census<\/a> on his podcast, The Sequel Show<\/em><\/a>. We covered everything from the overlap between interviewing and creating collaborative tech organizations to what a perfect KPI for data teams might look like.<\/p>\n\n\n\n

Whether you\u2019re a data analyst, an engineering manager, or are just interested in the changing face of interviewing, there\u2019s something for everyone in this conversation. Here are some of the highlights.<\/p>\n\n\n\n

Say goodbye to whiteboards and riddles. The future of technical interviewing is collaborative.<\/h2>\n\n\n\n

As CoderPad\u2019s Senior Analytics Manager, I live and breathe technical interviews. Yet I think we\u2019re constantly learning all that a live assessment can really do \u2014 for engineers, managers, and data practitioners alike.

Early on in our chat, Boris posed what might seem like a simple question: \u201cWhat, exactly, does a technical interview encompass?\u201d<\/p>\n\n\n\n

Boris and I have experience with organizations of all sizes \u2014 ranging from Microsoft all the way down to seed startups \u2014 and there has been a clear evolution of tech interviews over time. <\/p>\n\n\n\n

In the past, interviewers might have simply assigned sets of questions with strict criteria for answers. (Until recently, some big tech companies even used riddles in their interviews<\/a>.) Then came real-time whiteboard interviews<\/a>. While these did help to get a sense of a candidate\u2019s problem-solving style, they too often felt like a one-sided test.<\/p>\n\n\n\n

Now, we\u2019ve got something more useful. I outlined to Boris how, with CoderPad\u2019s interview platform, we strive to remove bias and let candidates work in their own style. (That\u2019s also part of why our live interviews support more than 30 programming languages<\/a>.)<\/p>\n\n\n\n

\u201cThe most useful part of a live technical interview is that \u2014 if done correctly \u2014 it can assess if a candidate matches the real, day-to-day responsibilities of a position. It puts interviewers and candidates on the same team. And with an analytics engineer, for instance, what better way is there to assess their true skills than by opening up a SQL pad and seeing what they can do?\u201d<\/em><\/p>\n\n\n\n

Most often, the person interviewing a potential engineer or data analyst isn\u2019t destined to be their boss, but instead a collaborator. So what\u2019s the point of making interviews feel adversarial? <\/p>\n\n\n\n

Interviewing is a two-way street. First, you need to decide if this candidate can do the job. But everyone involved is also assessing whether the person on the other end is someone they\u2019d enjoy working with. Let\u2019s face it: the old style of interviewing didn\u2019t help anyone figure that out. <\/p>\n\n\n\n

Live interviews can minimize stress at scale.<\/h2>\n\n\n\n

During our chat, Boris noted a fascinating tactic that he uses for assessing candidates at his current company, Census. In order to get a sense of how a late-stage interviewee might fit in with the broader team, he organizes a built-in hackathon.<\/p>\n\n\n\n

As he describes, this strategy reveals much more than just someone\u2019s technical skillset. More importantly, \u201cIt\u2019s about just working together. In a hackathon, we can\u2019t hide who we are as a company and, hopefully, it\u2019s clear by the end of it that we\u2019re on the same side as a candidate.\u201d<\/p>\n\n\n\n

The reason I found this so compelling is that it offers an organic way to get around one of the biggest problems in modern tech interviews: stress. Building the time to develop a rapport with someone, joke around a bit, and see their skills outside the confines of an assignment is invaluable. I view this as especially key with data specialists, who often end up floating between teams and need to feel comfortable working with broad sets of stakeholders.<\/p>\n\n\n\n

Unfortunately, Boris\u2019s method is hard to implement if you\u2019re hiring at scale. Conducting a hackathon in every interview is time-intensive\u2014taking up from four hours to a full day. But the core benefit of this style\u2013fostering a collaborative environment between the interviewer and the candidate\u2013is exactly how we at CoderPad see the future of technical interviewing. <\/p>\n\n\n\n

A collaborative CoderPad interview lets engineers and data analysts approach problems in their own way across languages. I outlined the advantages of our system like this:<\/p>\n\n\n\n

\u201cOnce we know someone is writing in R or Python or SQL, we can see what insights they produce and how they arrived there. This also mitigates bias from interviewers; with data from across hiring processes, it becomes less about seeing if a candidate answers how I, the interviewer, want them to. Instead, we can compare their process with other candidates.\u201d<\/em><\/p>\n\n\n\n

Now, collaboration can be baked in and all parties have something in common from the beginning. And it\u2019s not just candidates who prefer this method; we\u2019ve also gotten feedback from interviewers noting that interactive functions make prep far easier. Above all our hope is that, even if interviewing isn\u2019t always fun, it doesn\u2019t need to be painful. <\/p>\n\n\n\n

Make exploration part of your data team\u2019s process.<\/h2>\n\n\n\n

When it comes to modern data teams, it\u2019s easy to get caught thinking exclusively about day-to-day performance metrics. But Boris framed the deeper why?<\/em> for data professionals in an interesting way:<\/p>\n\n\n\n

\u201cData analysts have a choice to go to a consultancy, to work in-house, to go any number of directions. But I think what really draws them in is a huge opportunity to eventually answer questions that are currently fundamentally unanswered in the industry. That\u2019s super exciting.\u201d <\/em><\/p>\n\n\n\n

At CoderPad, we\u2019re motivated by an ambitious goal \u2014 improving technical interviewing \u2014 but our data team is in a unique position to ask questions in real-time along the way. So what data points do we collect? Our primary KPIs might seem simple on the surface:<\/p>\n\n\n\n