The ability to perform microbial detection and characterization in-field at extreme environments, rather than on returned samples, has the potential to improve the efficiency, relevance and quantity of data from field campaigns. To date, few examples of this approach have been reported. Therefore, we demonstrate that the approach is feasible in subglacial environments by deploying four techniques for microbial detection: real-time polymerase chain reaction; microscopic fluorescence cell counts, adenosine triphosphate bioluminescence assay and recombinant Factor C assay (to detect lipopolysaccharide). Each technique was applied to 12 subglacial ice samples, 12 meltwater samples and two snow samples from Engabreen, Northern Norway. Using this multi-technique approach, the detected biomarker levels were as expected, being highest in debris-rich subglacial ice, moderate in glacial meltwater and low in clean ice (debris-poor) and snow. Principal component analysis was applied to the resulting dataset and could be performed in-field to rapidly aid the allocation of resources for further sample analysis. We anticipate that in-field data collection will allow for multiple rounds of sampling, analysis, interpretation and refinement within a single field campaign, resulting in the collection of larger and more appropriate datasets, ultimately with more efficient science return.