If you have the full list and not just (for example) the significant genes, you can format your genes into the RNK format:
https://software.broadinstitute.org/cancer/software/gsea/wiki/index.php/Data_formats#RNK:_Ranked_list_file_format_.28.2A.rnk.29 and run GSEA Preranked on your data. Since your data is in Ensembl ID's you'd need to use GSEA's collapse function with the Human_ENSEMBL_Gene_ID_MSigDB.v7.4.chip. Also, it looks like your localization uses "," as a decimal separator, GSEA expects "." so you'd want to make that conversion. As to what you should use as the ranking metric itself, you have several options, commonly used are the Log2(FC), and the -log10(pValue)*sign(log2fc), but I might actually suggest using the wald test statistic that DeSeq2 produced there (the "stat" column). There isn't really a "right" answer in determining how to rank genes, the different methods just give you slightly different ways of looking at the enrichments in the data.