Your Data Hire Was Not Lost in Month Three. They Were Lost in Week One.

The resignation in month three started in week one

Most hiring managers can describe the loss the same way. The search took weeks. The interviews went well. The offer was accepted, the start date held, and then, somewhere around month two or three, the new data hire went quiet, then resigned. The file gets closed as a bad fit, and the search starts again from zero. What the file rarely records is the first week: the laptop that was not ready, the database access requested after the person arrived, the reporting tool license nobody had ordered, the manager who was travelling, and the new hire spending their first days reading old documentation and waiting to be told what mattered. None of that looks like a resignation cause. Together, it is often exactly that.

Data roles are unusually exposed to a weak start, because a data professional cannot do the job on goodwill. An analyst without access to the warehouse, the reporting platform, and the source systems has no work to show. A data engineer who does not know who owns a pipeline, where the definitions live, or which numbers the business trusts cannot safely change anything. A database administrator who has not been shown the backup routine, the alert history, and the known fragile jobs is not being cautious when they move slowly. They are being left uninformed. From the new hire's side, that first week answers a serious question: is this company organized enough for me to succeed here. If the answer looks like no, the decision to leave is often made early and simply acted on later.

What the evidence says about the first 90 days

Insight Global's 2025 Employee Sentiment Report, based on an independent survey of 905 United States workers in professional services, including technology and IT, found that 22 percent of workers have left a job within their first 90 days. Of those who left in that window, 60 percent said the primary reason was disorganized training or a lack of training. The same research found that 4 in 5 workers said they would stay longer in a role if they had better onboarding, and that workers take six to seven months to feel comfortable in a new role. Read those figures together and the management point is plain: onboarding is not a first week event. It is the first two quarters of the hire, and a fifth or more of hires are at risk early when it is disorganized.

Leaders see the same pattern from the other side. In Enboarder's 2025 HR Leader Survey, titled Winning the First 90 Days, 20.5 percent of HR leaders said up to half of their new hires leave within the first 90 days, and 60.8 percent said that early turnover had increased over the past year. The top reason HR leaders cited for 90 day departures was misalignment between job expectations and reality, at 30.3 percent, ahead of lack of connection with the team or company culture at 19.5 percent and a poor onboarding experience or lack of support at 17.4 percent. The survey also put a price on failure: a failed hire costs up to $25,000 by most HR managers' and directors' estimates, and closer to $50,000 by the estimates of chief human resources officers and chief people officers. For a specialized data role, the real bill is usually higher than the survey average, because the vacancy, the repeated search, and the work the team covers twice all sit on top of it.

The handoff is where it breaks

The weakest point is rarely effort. It is ownership. In the same Enboarder survey, only 36 percent of HR leaders described the handoff between recruiting, HR, and hiring managers as genuinely seamless, 28.8 percent had seen a hiring manager fail to provide a new hire with any guidance or training at all, and 44.8 percent of organizations provided only general guidelines for a 30, 60, and 90 day plan and left execution entirely to manager discretion. HR leaders also named clear role expectations as the top factor in onboarding success, with more than double the first place votes of any other factor. A data hire sits directly in that gap. Recruiting verified the skills, HR processed the paperwork, and the manager assumed someone had covered access, training, and priorities. When each party owns a piece and nobody owns the whole first 90 days, the new hire experiences the seams as one long delay.

What serious firms set up before and after day one

Firms that keep hard won data hires do not run a bigger welcome. They run a prepared start, owned by one named person, that treats access, clarity, and connection as deliverables with dates.

1. 1Order access before the start date and test it: laptop, network, database and warehouse permissions, reporting tool license, code repository, and ticket system, verified by an actual login, not a submitted request
2. 2Write the 30, 60, and 90 day plan in outcomes: what the hire will understand by day 30, own by day 60, and be accountable for by day 90, in language the hire receives on day one
3. 3Name one trainer or buddy who is not the hiring manager, with time set aside in the first two weeks to show how the data, the systems, and the team actually work
4. 4Give real, bounded work in the first two weeks: one report to rebuild, one pipeline to document, one data quality issue to trace, so the hire produces something visible early
5. 5Write down the tribal knowledge: key definitions, data owners, known bad data, fragile jobs, and the reports leadership trusts, instead of leaving it to be discovered by accident
6. 6Hold short check ins at day 7, 30, 60, and 90 with the same two questions: what is blocking you, and what does this job need that nobody has shown you yet, then close what surfaces

Two points in that sequence carry more weight than the rest. First, the expectations set at interview have to match the job that onboarding reveals. Misalignment between expectations and reality was the single largest reason HR leaders gave for 90 day departures, and onboarding is where that gap is either closed honestly or discovered badly. If the role involves cleaning up undocumented pipelines, covering reporting requests, or working with a lean team, the first month should show that work plainly, with support around it, rather than protect a tidier story told during hiring. Second, early work has to be real. A new data hire given only reading and shadowing for a month learns that the company does not yet trust them with anything that matters, and skilled people read that signal quickly. One bounded, visible piece of work, reviewed supportively, does more for retention than any welcome event.

What this means if you are hiring in Oklahoma

In Oklahoma, an early exit costs more than the national survey figures suggest, for a simple structural reason. The local pool of experienced data engineers, analysts, and database professionals is smaller, so a hire lost in month three is not replaced from a standing shortlist. The search restarts, the role sits open longer, and the same lean team that covered the vacancy the first time covers it again, now with the added work of a second onboarding behind them. Lean teams also feel the ownership gap first. There is often no onboarding department and no spare coordinator, which means the first 90 days run well only if the hiring manager deliberately owns them. That is a disadvantage when it is left to chance and a real advantage when it is handled directly, because a local hire can meet the team, see the systems, and get straight answers from the people they will work with, without layers in between.

At Oklahoma Data Partners, our recruiting work does not end at the accepted offer. We are data practitioners, so we help employers define the role honestly, verify skills with real work, and set up the first 90 days so a new data hire can actually do the job they were hired to do: access ready, expectations written down, and a named person accountable for the start. If you have hired data talent and lost them early, or you are about to open a search you cannot afford to run twice, book a consultation and we will walk through where your first 90 days are most likely to break.