Third Time’s the Charm: Finding a Data Engineering Manager for a Global Insurance Company
A global insurance company came to us with a search that had already defeated two previous attempts. They needed a Data Engineering Manager to take the reins on an in-flight platform build, and after years of not quite finding the right person, they needed someone who would approach it differently. Five weeks later, the right candidate had accepted the offer.
The Challenge
The company was mid-way through building out a cloud and Databricks platform solution, and they needed the right person to help steer it to completion and beyond. The role was a genuine blend of hands-on technical leadership, team management, and senior stakeholder engagement — and getting that balance right was critical.
This was not a purely technical role, nor was it a purely managerial one. The incoming Data Engineering Manager would need to lead from the front, getting involved in the detail of the platform build while also managing a small team and holding themselves accountable for the function as a whole. Senior stakeholders would need to be kept informed and confident throughout.
What made the search harder was the history behind it. The company had tried to fill the role twice before, and on both occasions the brief had been drawn too broadly. Previous searches had been aimed at generalist profiles rather than the specific kind of person the role actually demanded. That meant the talent pool had been searched in the wrong places, and the right candidates had never been surfaced.
The Approach
From the discovery session, one thing came through clearly and repeatedly: this person needed to lead from the front. That phrase came up several times, and it shaped everything about how we approached the search. We were not just looking for someone with the right technical credentials — we were looking for a specific type of person, someone with the personality, the drive, and the proven track record to take ownership and push things forward.
That narrowed the target considerably. We ran a dedicated headhunt campaign focused on candidates, both known and unknown, who had either personally built out a data platform or been at the sharp end of a team that had. Similar insurance companies were the natural hunting ground, and we went after that market directly rather than waiting for applications to come in.
Given how specific the remit was, the qualification process took time. A fair number of candidates needed to be thoroughly assessed before we could confidently put people in front of the client, and we worked closely with them throughout to ensure alignment on what the right profile looked like. That kind of collaboration between recruiter and client is often what separates a successful search from another one that falls short.
The campaign drew on both our existing network and candidates identified through proactive outreach. Together, they produced the shortlist that ultimately delivered the hire.
The Result
From instruction to accepted offer, the search took five weeks. Given the complexity of the brief and the fact that two previous attempts had not succeeded, that is a strong outcome.
The difference this time was precision. Rather than searching broadly and hoping the right person would emerge, we defined exactly what was needed, went after that profile specifically, and worked with the client to validate candidates against the full scope of what the role demanded.
What This Tells Us About Specialist Data Engineering Hiring
Roles that sit at the intersection of hands-on technical delivery, team leadership, and stakeholder management are genuinely difficult to fill. The people who can do all three well are not always visible in the market, and they are rarely actively looking. A headhunt approach, targeting candidates in comparable environments who have already done what the client needs done, is usually the only reliable way to find them.
Broad briefs and generalist searches will not get there. Understanding what the role truly requires, and going after that profile with focus and intent, is what makes the difference.
Working on a complex data or engineering hire that needs a more targeted approach? Get in touch with the Nexus Spark team to talk through how we can help.