Why does a data vacancy stay open for months?

A data vacancy usually stays open for four reasons: the role asks for two people instead of one, the requirements describe the past instead of the work, nobody actively leads the conversation with candidates who are not searching, and the vacancy does not show what makes your company special. All four can be fixed without raising the salary.

7 August 2026 · updated 9 August 2026 · 5 minutes read

NewData

An introduction meeting with a candidate — Image generated with AI.

Contents

A data vacancy that stays open for six months is rarely a matter of scarcity. There are plenty of data analysts and data engineers; they simply do not respond to this vacancy. In the conversations we have, the same causes keep coming back, and every one of them can be fixed without raising the salary.

Cause

Does the vacancy actually ask for two people?

Data engineering, building dashboards, taking stakeholders along and also putting a model into production. Whoever can do all of that already has a job and is unaffordable. We call that the five-legged sheep.

Whoever does apply can do part of it well and the rest passably, and is therefore rejected by many recruiters and HR departments. That is how a vacancy becomes hard to fill: the requirements exclude everyone who would fit.

The solution? Split the role. A data engineer who builds pipelines and a data analyst who creates the insight are found faster together than one person who has to do everything. The second role is often temporary too: half a year of capacity is enough to clear the backlog.

Cause

Do the requirements describe the work or the past?

Five years of experience with a tool that has existed for three. A certification nobody on the team holds. Requirements like these do not filter quality, they filter coincidence.

Rather describe the work your candidate will do in the first six months. What is ready to pick up, what is the first assignment, who sits next to them for guidance? People recognise themselves in that, and it makes selection fairer: you judge on what someone is going to do instead of on what someone happened to encounter before.

Cause

Is anyone leading the conversation, or is the ad just sitting there?

Many good data professionals are not actively searching. They have work, they are approached weekly, and they respond to a good conversation, not to an advertisement.

Without someone actively leading that conversation, the vacancy stays open however well it is written. That is exactly what NewData Search exists for: searching actively, selecting on subject matter and culture fit, and staying involved after the placement.

Cause

Does a candidate recognise your company in the vacancy?

Culture fit is the phrase that comes up in every recruitment conversation and returns in almost no vacancy text. A candidate who reads the text should be able to think: “this is where I want to work”. Not for the salary, but for the company and the people who work there.

So write down what is different at your place. What a working day looks like, where colleagues run into each other, what you are proud of and where things are still messy. Someone who knows in advance what is expected of them and what they bring, applies with a different feeling than someone who only read a job profile.

The outcome

What does fixing this deliver?

A shorter lead time, but above all: fewer people who leave again after half a year. A placement is not an end point, it is the start of a relationship.

If you doubt whether it is the vacancy or something behind it, the NewData Bedrijfsscan is the starting point. In one working day we map how data, processes, systems and people come together at your organisation, and where exactly the role is missing.

Questions

Frequently asked questions

How long may a data vacancy stay open?

For a data analyst or BI specialist, six to eight weeks is normal. If a vacancy stays open longer than three months, it is almost always down to the vacancy text or to the absence of active outreach. Our experience is that even vacancies with a weaker salary package get responses, as long as the rest is right.

Does a higher salary fill a data vacancy faster?

It can help to attract talent quickly, but in practice we see those people leave again just as quickly. The package of salary and benefits obviously has to be right, but a higher salary is rarely a guarantee of a lasting relationship. A more sharply defined role works better and costs less.

What is the difference between a data analyst and a data engineer in a vacancy?

A data analyst translates figures into decisions. A data engineer builds the pipelines those figures come from. Whoever puts both in one vacancy is looking for two people at once.

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Labels: vacancies, recruitment and selection, data analyst, data engineer, labour market.