Data Engineering for Recruitment & HR Tech

Orqent Labs builds the unglamorous layer properly, ingestion, modelling, quality and lineage, because everything above it inherits whatever we get wrong here.

In recruitment & hr tech, any screening automation must be tested for bias and be explainable to a rejected candidate. That single fact reshapes how data engineering has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.

The workload we are most often asked to take on first is CV parsing and structured screening, usually integrated against ATS. We build the smallest thing that proves the case, put it in front of real users, and expand only what earns its keep.

Multi-model by default, so a provider outage is a routing decision rather than an incident. Six weeks to something running in production, not six quarters to a strategy document.