Martech Skill Sets: What You’re Hiring For Is Probably Wrong

Most marketing teams hire for martech the same way they buy martech: they look at the feature list, match it to a job description, and move on. The result is a team full of people who can operate tools but cannot tell you whether those tools are working. If you want martech to deliver commercial value, the skill sets you hire for need to go well beyond platform proficiency.

The gap is not technical. It is analytical and strategic. The marketers who get the most out of a martech stack are the ones who can interrogate the data it produces, connect it to business outcomes, and make decisions when the data is incomplete, which is most of the time.

Why Martech Hiring Keeps Producing the Wrong Results

I have sat across the table from hundreds of candidates over the years, and I can tell you that the martech hiring process is broken in a very specific way. Most job descriptions are written by someone who has just audited the current stack and listed the tools as requirements. Salesforce Marketing Cloud experience: required. HubSpot certification: preferred. Marketo proficiency: a bonus. What you end up with is a shortlist of people who have clicked around in the same platforms you already have, without any evidence that they made those platforms produce better outcomes.

When I was growing an agency from 20 to just under 100 people, we made this mistake early. We hired based on tool familiarity because it felt safe and fast. The problem was that tool familiarity has a short shelf life. Platforms change, stacks evolve, and the person you hired to run your marketing automation is suddenly managing a different system eighteen months later. If the only thing they brought to the role was knowing the old one, you are back to square one.

The martech landscape has also become genuinely complex. The intersection of data, privacy, automation, and AI means that the skills required to operate a stack effectively in 2025 look very different from what was needed five years ago. Forrester has written about how org chart design reflects strategic priorities, and the same logic applies to hiring. The roles you create and the skills you recruit for are a direct signal of what you think martech is actually for.

The Skill Sets That Actually Move the Needle

There are four categories of skill that I have consistently seen separate high-performing martech hires from average ones. None of them are about knowing a specific platform. All of them are about how someone thinks and what they do with information.

Critical Thinking and Analytical Rigour

If I had to pick one skill to prioritise above everything else in a martech hire, it would be critical thinking. Not data literacy in the narrow sense of being able to read a dashboard, but the deeper capacity to question what a dashboard is actually measuring, whether that measurement is meaningful, and what it is leaving out.

I spent several years judging the Effie Awards, which are as close as marketing gets to a rigorous effectiveness benchmark. One of the things that struck me consistently was how many entries conflated correlation with causation, and how few teams had genuinely interrogated whether their martech was driving outcomes or just recording activity that would have happened anyway. The teams that stood out were the ones who had someone on staff asking uncomfortable questions about attribution, about channel interaction effects, and about what the data was not capturing.

That capacity is rare. It is also not something you can train into someone who does not already have the instinct. When you are interviewing for martech roles, ask candidates to walk you through a time when the data told them one thing and they concluded something different. If they cannot answer that question with a specific example, they are probably an operator, not an analyst.

This connects to a broader point about marketing operations as a discipline. If you want to understand how the best teams are structuring this function, the Marketing Operations hub at The Marketing Juice covers the commercial and strategic dimensions that most martech content ignores.

Commercial Awareness

Martech exists to support commercial outcomes. That sounds obvious, but in practice, most martech teams operate at a significant remove from the business metrics that actually matter. They are measured on platform utilisation, email open rates, lead volumes, and automation throughput. They are rarely measured on revenue contribution, customer acquisition cost, or lifetime value.

The hires who close that gap are the ones who understand how marketing connects to the P&L. They know what a customer costs to acquire, what they are worth over time, and what the margin implications are of different channel mixes. They can sit in a commercial planning meeting and contribute something useful, rather than waiting to be told what the targets are and then building workflows to chase them.

When I was running agencies, the martech and operations people who had the most influence internally were the ones who could talk to the CFO without needing a translator. They understood that every platform licence, every integration, and every campaign automation had to justify itself in terms of return, not just functionality. That commercial grounding changes how you configure a stack, how you prioritise integrations, and how you make the case for investment.

Commercial awareness is also what allows martech professionals to push back when a request does not make sense. Unbounce has a useful framing of how inbound marketing processes should connect to business outcomes, and the same logic applies to martech decisions. Every configuration choice should trace back to a commercial objective. If it does not, someone needs to ask why it is being done at all.

Data Governance and Privacy Fluency

This is the skill set that most hiring managers underweight, and it is increasingly the one that creates the most operational risk when it is absent. Privacy regulation has changed the technical requirements of martech significantly. Consent management, data residency, suppression logic, and first-party data strategy are no longer edge cases. They are core to how a stack needs to be built and maintained.

The problem is that most martech professionals learned their craft in an era when data collection was largely unrestricted and third-party cookies were the default. Many of them have not genuinely updated their mental models to account for what a consent-first data environment requires. They can configure a CRM, but they cannot tell you whether the data in it was collected in a way that is legally defensible.

Privacy questions in martech are not just legal questions. They are technical and strategic ones. Mailchimp’s SMS and email privacy guide is a useful starting point for understanding what compliant data practices look like at a practical level, and the kind of thinking it requires should be embedded in your martech team, not outsourced to legal. The people configuring your automation need to understand why certain data practices create risk, not just be told to follow a checklist.

When you are hiring, look for candidates who can speak to first-party data strategy with some specificity. Ask them how they have approached consent management in a previous role. Ask them what they do when they inherit a database that was built under different data practices. The answers will tell you a great deal about whether they understand the current environment or are still operating with an outdated mental model.

Cross-Functional Communication

Martech does not operate in isolation. It sits at the intersection of marketing, sales, IT, finance, and increasingly legal and compliance. The people who run it need to be able to communicate effectively across all of those functions, which means translating technical outputs into language that different stakeholders can act on.

This is a skill that is genuinely difficult to hire for because it is not visible on a CV. Someone can have an impressive list of platform certifications and no ability whatsoever to explain to a sales director why the lead scoring model is producing the results it is. Conversely, someone with a less technical background but strong communication instincts can add enormous value by bridging the gap between what the stack is doing and what the business needs to understand about it.

I have seen martech investments fail not because the technology was wrong but because no one on the team could make the case for it internally. The platform was configured well, the data was clean, the automation was running, and the senior leadership team had no idea what any of it was contributing because nobody had connected it to the numbers they cared about. That is a communication failure, and it is one that costs teams budget, headcount, and credibility.

If you are building a martech function from scratch or rebuilding one that is underperforming, put someone in the team whose explicit job is to translate. Not to manage platforms, not to run campaigns, but to make sure that the outputs of the stack are legible to the people who control the resources. HubSpot’s research on what actually lands with CMOs reinforces a consistent theme: senior leaders respond to commercial clarity, not technical detail.

How to Rewrite Your Martech Job Descriptions

The fastest way to attract better martech candidates is to change what you lead with in the job description. Most martech JDs open with a list of platform requirements and close with a vague statement about being a team player. Flip that structure entirely.

Start with the business problem the role is designed to solve. Not “we are looking for a marketing automation specialist” but “we are building a first-party data capability and need someone who can design the architecture, manage the governance, and connect it to our acquisition and retention strategy.” That framing attracts people who think about outcomes, not just people who want a job that matches their existing tool set.

Then be specific about the analytical expectations. If you want someone who can interrogate attribution models, say so. If you need someone who can present to the CFO, say so. If you expect the role to own the commercial case for the stack, make that explicit. Vague job descriptions produce vague candidates.

Platform requirements should appear in the job description, but they should be framed as context rather than criteria. “We currently use HubSpot and Salesforce” is useful information. “Must have five years of HubSpot experience” is a filter that will exclude good candidates who have done the same work in different platforms and include mediocre candidates who happen to have spent time in the right tools.

Forrester’s work on marketing planning maturity is relevant here. The organisations that get the most from their martech investments tend to be the ones that plan with commercial rigour, and that rigour needs to be embedded in the team from the hiring stage. You cannot plan commercially if you have hired technically.

The Interview Process Most Teams Get Wrong

Most martech interviews are essentially platform demos. The candidate is asked to walk through how they would configure a workflow, what their experience with a particular integration is, or how they have used a specific feature. These are reasonable questions, but they test operational knowledge, not the skills that actually determine whether someone will add value.

A better interview process for martech roles includes at least one session that is explicitly about commercial thinking. Give the candidate a scenario: the stack is producing a certain volume of leads, but the sales team is not converting them at the expected rate, and the CMO wants to know why. What do they do? How do they approach the diagnosis? What data do they look at? What assumptions do they challenge? What do they recommend?

The answer to that question will tell you more about whether someone can do the job than any discussion of platform features. You are looking for someone who asks clarifying questions before jumping to conclusions, who considers multiple explanations before settling on one, and who understands that the martech stack is one possible source of the problem but not necessarily the most important one.

I would also include a data interpretation exercise. Give candidates a real or realistic data set from your stack and ask them to tell you what it means. Not just to describe what they see, but to tell you what they think is driving the numbers, what they are uncertain about, and what they would want to know that the data does not show. That last part is the critical thinking test. The candidates who tell you what the data is missing are almost always more valuable than the ones who can only describe what it contains.

Building a Martech Team That Thinks, Not Just Operates

If you are building or restructuring a martech function, the goal is a team that can think its way through problems, not just execute against a playbook. That means you need a mix of profiles: someone with deep technical fluency who can build and maintain the architecture, someone with strong analytical instincts who can interrogate the outputs, someone with commercial awareness who can connect everything to the P&L, and ideally someone who can communicate across all of those dimensions to the wider business.

In a small team, you will not always get all of those in separate people. But you can hire for the combination of skills that matters most for your current stage. An early-stage martech function probably needs the analytical and commercial skills more than deep technical depth, because the most important decisions are about what to build and why, not how to configure it. A more mature function that already has a working stack probably needs to invest in the governance and communication skills that will protect what has been built and make it legible to the business.

The common thread across all of those profiles is intellectual honesty. Martech produces a lot of data, and a lot of that data is ambiguous, incomplete, or misleading if you do not understand its limitations. The people who will serve you best are the ones who are comfortable saying “I do not know” when they do not know, and who treat the stack as a tool for improving decisions rather than a source of answers.

For a broader view of how marketing operations functions are evolving and what the best teams are prioritising, the Marketing Operations section at The Marketing Juice covers the strategic and commercial dimensions that rarely appear in vendor content or platform documentation.

About the Author

Keith Lacy is a marketing strategist and former agency CEO with 20+ years of experience across agency leadership, performance marketing, and commercial strategy. He writes The Marketing Juice to cut through the noise and share what works.

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