Building out a technical team is a huge undertaking. Not only do you have to evaluate for skills and technical knowledge: you also have to curate a team that can work well together.
Ultimately, creating a harmonious, productive team is a function of two basic variables:
A team of skilled individuals that can’t work together is like a can of premium gas without a car to put it in. Having it is an essential step to forward movement: but you won’t have much luck getting it from point A to B without the car.
Mismatched teams not only bode poorly for each individual’s future performance—they also heighten the risk of short tenures. Otherwise put: teams run the risk of huge time losses, stuck hiring the same roles over and over.
If you find yourself struggling to put together compatible, productive teams, bookmark this resource for later. And if you’re short on time, tide yourself over with cliff notes:
As tech stacks become more and more fragmented, the line between some specialized technical roles is admittedly blurry.
Take, for example, the difference between data analysts and data scientists. A data analyst and data scientist might both be focused on interpreting data for non-technical stakeholders. But a data analyst might focus on interpolating historic data, whereas a data scientist might focus on extrapolating predictions from historic data. And especially at smaller companies, a data scientist might even be doing both.
Ultimately, this challenge boils down to misalignment between hiring managers and recruiters. Historically, research has shown that aligning on expectations is hiring managers’ biggest hurdle.
Even if you’re recruiting for a role that you’ve seen a dozen times before, don’t assume that the ask is the same. Take the time to deep dive on each individual role, and understand the finer points they need in order to be successful long-term.
Emotional intelligence (or, EQ) is a way to describe the ability to identify and manage your emotions, plus the emotions of others. It’s an important indicator of how candidates will conduct themselves on the job: it’s shown strong correlation with job performance, and leadership capabilities—and much more.
But when it comes to technical roles, most recruiters are focused more on on technical skills, less on potential EQ signals, like endorsements from past co-workers. And on some level, that’s fair: after all, finding qualified candidates is the most time consuming part of hiring for both hiring managers and recruiters.
Ultimately, the best way to emphasize EQ is to make the time for it. Establish a process to vet technical skills systematically, and uniformly. The less time you spend on verifying a candidate’s stated skills, the more time you can spend getting to know them as a person.
Let’s say you’re hiring a senior back-end developer. You’re looking for:
And you see a candidate with the following qualities:
On paper, this candidate might look great: after all, they have the skill set that you’re looking for, and they’re seasoned enough to be independent. But we can catch a few red flags:
full-stack capable, but back-end focused
Have they ever worked with a front-end developer, or are they used to doing the work themselves? Do they know how to communicate with them in a meaningful way to get things done? How much ownership do they expect to have over the process?
career spent working with small teams (teams of 3-5 developers total)
Coming from a small company means the candidate is likely to be self-sufficient. But are they too self-sufficient? How do they work in a team? Do they openly collaborate with others, or do they tend to silo themselves off from the group? Neither option is bad––but one might be a better fit for your team than the other.
Finding developers with the right mix of technical skills, soft skills, and team compatibility can be a challenge, at best. This is just the abridged version. Want to dig deeper?
Learn more about how to build rock solid teams with recruiter cheat sheet. We explore what to expect from key technical roles, how to build compatible teams, plus data on what languages and frameworks developers know best: