When you spend time reviewing CVs for a data role, you notice something fairly quickly. There are a lot of people out there with strong technical knowledge who are probably brilliant at what they do. And yet something is often missing: while their technical potential is unquestionable, the critical thinking that turns it into real business impact hasn’t caught up yet.

If everything someone can think of is a technical solution, that is a problem. Data work exists to help businesses make better decisions. That requires someone who can walk into a brief and ask whether it is the right brief. Someone who understands the commercial context before reaching for the data. Someone who takes end-to-end accountability for business impact rather than simply shipping deliverables. These things are very hard to find, and they do not show up on a CV.

Developing an eye for it in a hiring process is genuinely tough. It comes through in how someone talks about a problem, what questions they ask, whether they reach instinctively for the business context or jump straight to a technical answer. It is one of the harder skills in building a data team, and most hiring processes are not set up to test for it.

If somebody has decided they want to be a data professional, they usually already have a knack for the technical side. SQL improves with time. You start thinking about query costs, partitioning, data governance. Data scientists work through more model types and methodologies as their careers develop. These things come naturally enough if the foundation is there.

What does not come automatically is the behavioural side: business context, problem thinking, ownership of outcomes, communication that actually changes what a client does, and self-awareness about what is missing. These require deliberate effort in a way that picking up a new tool does not. And they are rarely talked about explicitly in data career frameworks, which tend to focus on the technical side because that is easier to define and easier to measure.

Most data professionals do not lack technical skills to progress. What is actually holding most people back is the behavioural component.

This became a practical problem for us. We had an evaluation framework that listed specific technical skills, such as knowing Python, and being able to build a certain type of report. The usefulness of that technical criteria had an inverse correlation with seniority however: as the team grew and became more experienced, individuals required greater breadth in the skills they were assessed against. They required more colour on what they needed to develop, what progression looked like, and what they needed to do to take on more responsibility. A list of technical skills alone could not answer those questions.

We tried redefining things at a product level and hit walls. So we went back further. We mapped out our entire data ecosystem: every capability area, every domain, every tool and methodology that matters in performance marketing data work. That became the foundation for a proper technical skills map, covering nine knowledge domains, each with a proficiency scale from awareness through to authority, with different expectations by role rather than one generic standard applied to everyone.

But as we worked through it, a pattern kept emerging. Technical proficiency alone was not telling the whole story. There were people who could do the work at a high level but were not quite ready for more responsibility, and the technical framework could not explain why. The gap was behavioural. How they thought about problems, how they communicated, whether they took real ownership of outcomes. That pushed us toward building a second part of the framework: a set of behavioural expectations that apply to every role, every level, every specialism. Six themes, defined at every level from intern to director, with specific observable behaviours rather than vague aspirations.

To make this concrete, take Ownership and Delivery. On paper, everyone at every level is expected to deliver their work. In practice, what that means looks completely different depending on where someone is in their career.