Case studies

A Series A business, seven years old, going through an incubator health check ahead of a Series B to scale from 90 to 200 people. Three founders: CEO, CTO and Head of Engineering.

The Head of Engineering was burnt out, after almost eight years of 12-hour days architecting the platform and building an engineering team of over 60 people.

As they had scaled, they had built up technical and people debt, including on DEI.

Part of the Series B deal was that, for the company to grow to around 200, the Head of Engineering would move to Chief Architect and give up people management. They needed a new engineering leader who could level up on DEI and had the time to be more people-focused.

Our remit was to find the Head of Engineering's replacement, confidentially.

The challenge was two-fold.

The new Head of Engineering needed strong engineering experience, to be credible with the senior engineers, along with strong people skills and a wish to focus only on people management.

And they had to be willing to step down from pilot to co-pilot for a while.

The search was confidential. Morale at tech lead level was already a problem: they had grown quickly, made some mistakes, and built up people debt and churn.

A profitable, bootstrapped Big Data agency, four years old, selling data with vast numbers of touch points to high-end construction companies. All of it was generated and wrangled by hand by a large team of data engineers, which limited what they could sell and to whom. They were turning away smaller, potentially better-quality work. Labour-intensive, but lucrative.

Leadership saw they could take a much bigger share of the SME market if they automated the product and sold it through self-service web portals: lower value, higher volume. That meant changing the business model from agency to SaaS.

They also had to move from on-prem servers to AWS. A complete change of business model, with a lot that could go wrong.

To make it happen they needed a Head of Data with SaaS experience and, first and foremost, a Lead Platform Engineer.

The Head of Data had to pull everything together: people management experience to run the large data team, and AWS knowledge from a commercial angle, working closely with the CEO and joining business development in a pre-sales capacity.

By the time we were engaged they had already hired and let go of one person, and spent seven months with recruitment agencies that, for various reasons, didn't deliver.

Their job description generated 100+ data people every month, without fail. All of them had functional data experience, not commercial.

Our candidate was interviewed within a week and had an offer in week three.

The CEO told us after the first interview: "I wanted to offer her the job halfway through the interview but didn't want to lose my dignity!"

As we profiled the role, it became clear this was no ordinary Platform Engineer role.

All of the company's data sat on bare-metal Linux servers on-prem.

The Lead Platform Engineer had to be an AWS and cloud services specialist, a Linux expert, and confident enough to take responsibility for the migration.

Except most Lead Cloud Platform Engineers still hands-on had started in cloud, not Linux, and anyone with that Linux experience would have been promoted away from hands-on work years ago.

Where do you find someone like that?

Red Hat, of course.

A big-brand supermarket and online retailer had advertised the role for four months and exhausted its pipeline when we stepped in. Cyber security was a hot sector, architects especially, and the competition was heavy.

Job descriptions are often hard to tell apart, and the best candidates, by their indifference, agreed.

The role listed too many responsibilities and too many required skills. It was impossible to tell what it actually focused on.

We broke it into five key areas and weighted each by the time likely to be spent on it and the level of experience required. That gave us, and the candidates, a clear picture of the work at both the macro and the micro level.

Then we looked hard at where the role offered professional growth. Most roles of this type look the same, so that was where it could stand apart.

From this we built a profile of the person we were looking for and the case we would make to them, and set to work.

We had a shortlist of five within three weeks, and the role was filled in week six.

Founded in 2019, 50 staff. They work with manufacturers using robotics, building AI that makes prototyping and production possible within days, at low cost.

They had been interviewing for three months without success.

We reviewed what they were using to attract candidates, then rebuilt the job description around what the role offered, not only what it asked for. We agreed together where the ideal candidate would be in their career, and what would count as a step forward for them.

We contacted a long list of 50 and narrowed it to 10, and interviewed all 10 against the same three questions. Three made the shortlist and spent a few hours with the teams.

We prepared their preferred candidate for an offer and negotiated terms that worked for both sides.

The search was completed in five weeks.