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Objectives: Using whole genome sequencing of SARS-CoV-2 to identify variants circulating in DRC and obtaining molecular information useful for diagnosis, improving treatment and general pandemic control strategies. Methods: Seventy-four SARS-CoV-2 isolates were sequenced using Oxford Nanopore platforms. Generated reads were processed to obtain consensus genome sequences. Sequences with over 80% genome coverage were used for variant calling, phylogenetic analysis and classification using pangolin lineage annotation nomenclature. Results: Phylogenetic analysis based on Pangolin classification clustered South Kivu sequences into seven lineages (A.23.1, B.1.1.6, B.1.214, B.1.617.2, B.1.351, C.16 and P.1). The Delta (B.1.617.2) variant was the most dominant and responsible for outbreaks during the third wave. Based on Wuhan reference genome a total of 289 distinct mutations were detected including 141 missenses, 123 synonymous and 25 insertions/deletions when our isolates were mapped to Wuhan reference strain. The majority of these point mutations were located within the coding sequences of the SARS-CoV-2 genome that includes Spike, ORF1ab, ORF3, and nucleocapsid protein (N) genes. The most common mutation was D614G (1841A>G) observed in 61 sequences followed by L4715L (14143C>T) found in 60 sequences. Conclusion: Our findings highlight multiple introductions of SARS-CoV-2 into South Kivu through different sources and subsequent circulation of variants in the province. These results emphasize the importance of timely monitoring of genetic variation and its effect on disease severity. This work set a foundation for the use of genomic surveillance as a tool for future global pandemic management and control.