A Komprise survey found that only 4% of organisations have created schema for more than 70% of their unstructured file data and made it accessible to lakehouse and analytics teams. Just 24% have even made a start. The platforms are live. The legacy files are still locked away.<\/p>\n
A Munich logistics company asked us recently for someone who could catalogue and schema-map a decade of operational files sitting in on-premises storage. The lakehouse was running, the dashboards were built, but the analytics team was working from a fraction of the available data because nobody had done the work of making the rest queryable. That search took longer than the original platform hire.<\/p>\n
Data engineers who can handle unstructured file integration sit somewhere between traditional data engineering and information management. The work involves understanding file metadata, designing schema that preserve context, and building ingestion workflows that handle volume without choking. Candidates with that profile often come from document management or enterprise content backgrounds rather than pure analytics pipelines. When we run searches for these roles, we look outside the usual lakehouse talent pools.<\/p>\n
Hiring managers across the DACH region should consider treating unstructured data integration as a dedicated workstream with its own headcount rather than a task for the existing lakehouse team. The 96% of file data that remains inaccessible in most organisations represents years of integration work. Companies that staff for it now will extract value from archives their competitors are still ignoring.<\/p>\n