The queen snapper, Etelis oculatus, is experiencing a growing fishery presence across the wider Caribbean, yet our understanding of its distribution, biology, and ecology remains limited. To address this gap, we investigated the feeding ecology of this demersal deep-water snapper using two molecular approaches: single-species barcoding and multispecies metabarcoding. Between November 2019 and July 2020, we collected 157 queen snapper from seven locations along the west coast of Puerto Rico. Our analysis identified a diverse array of prey items in the stomachs, comprising 61 species from 31 families, 18 orders, and 38 genera. Our findings suggest that E. oculatus is a large carnivore, primarily preying on squids, shrimps, and deep-water fishes. Notably, common fish prey included Diaphus brachycephalus, D. dumerilii, Dasyscopelus selenops, Coccorella atlantica, Sigmops elongatus, and Zaphotias pedaliotus. In contrast, prevalent invertebrate prey consisted of Abralia veranyi, Doryteuthis pealeii, Abralia redfieldi, Oplophorus gracilirostris, and Systellaspis debilis. Although our data suggest potential variation in diet composition across locations, definitive conclusions remain elusive. However, we observed heightened prey richness at seamount Pichincho, possibly attributable to the high structural complexity of the karst terrain on the seafloor. Additionally, we noted variation in prey species composition across size classes, with certain species more prevalent in larger or smaller queen snapper. Given the challenge of examining the prey of deep-water fish species, our study showcases the utility of both single-species barcoding and multispecies metabarcoding methodologies in characterizing the dietary range of queen snapper and similar demersal deep-water carnivorous fishes. The multispecies metabarcoding approach, in particular, offers a rapid, comprehensive, and effective means of identifying prey species. As the commercial value of the queen snapper continues to rise, our investigation into its feeding behavior provides critical baseline information for future species management efforts. By enhancing our understanding of its ecological dynamics, we aim to contribute to informed conservation and sustainable fisheries practices in the region.