Why data engineers are becoming private equity’s most strategic asset

4 days ago 1
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Getting data engineers to contribute to commercial thinking could radically increase the technical efficiency of private equity firms.

Data engineers could be the private equity firm’s hidden weapon, argues JMAN Group’s Leo Valan – if only they were listened to more.(Image: Shutterstock)

In most private equity (PE) firms, data engineers are still viewed primarily as technical support, tasked with building pipelines, cleaning data and generating reports. This is increasingly becoming an untenable approach. If firms want to unlock the value of data, they need to bring data engineers to strategic discussions early on. When treated as commercial partners rather than backend technicians, data engineers can help uncover insights, bridge data gaps and drive value.

There’s been a lot of talk recently about firms becoming more data-driven. In practice, however, that often just means collecting more information. Large volumes of data get pulled in, stored and surfaced in dashboards, but not always for the clearest of reasons; it’s often easy, after all, to end up measuring what’s convenient rather than what’s genuinely useful. Far too often, engineers are asked to fetch metrics or maintain data platforms, only to be given limited visibility into the decisions those metrics are meant to support or why they actually matter.

That separation is a problem. The engineers closest to the data are often the ones best placed to notice when something isn’t quite right. They can see where definitions are inconsistent, where noise is hiding the signal or where something important isn’t being tracked at all. If they’re not included in wider team discussions, those observations rarely get raised and almost never acted upon. What you’re left with is surface-level reporting that ticks a box but misses the real issues.

The firms that are getting this right have made space for engineers to contribute to commercial thinking. That might mean joining diligence calls, shaping the data workstream in value creation plans or reviewing monthly performance data with the ops team. Engineers don’t need to think like investors; they just need enough context to make their work relevant.

Sometimes the impact is subtle: helping a portfolio company spot delays in customer onboarding, for example, or identifying a pricing inconsistency across territories. Other times, it’s more significant. We’ve seen examples where engineers flagged usage patterns of investment teams from dashboard analytics that raised questions about the assumptions in a deal model. In one case, it led to a price adjustment during negotiations. These examples aren’t rare; they’re what happens when engineers are involved in the right way.

Bringing data engineers into the tent

To get this right, firms need to think differently about hiring and integration. Technical skills matter, but so does mindset. You need people who are curious about how the business works and comfortable questioning things when they don’t seem right, even if no one else is saying anything.

At the same time, deal teams need to be open to those questions. There’s little point in hiring capable people and then asking them to sit in the background. Some of the most useful challenges come from outside the core deal team, from someone looking at the data with fresh eyes, not anchored to the same assumptions.

No one’s expecting engineers to become analysts or take over commercial decisions. But their deep understanding of how data is structured – what it reveals, what it lacks and where the gaps lie – is invaluable. Without their input, critical nuances can be overlooked. When data engineers and commercial teams work together, the quality of analysis improves significantly. You catch issues early and act with more confidence.

Private equity moves fast. There isn’t always time to spin up a full analytics project. That’s why it helps to have engineers who are already close to the work, already understand the context and can spot something early before it becomes a problem or notice something useful before anyone else does.

The firms involving engineers properly are already seeing the benefit. Others are still building out infrastructure, but seeing little value from it – mostly because the people who could make it useful haven’t been brought in.

Leo Valan is the chief technology officer for JMAN Group

Read more: To adopt AI, banks must first define the problems it’s meant to solve

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