It's a boring answer, but the answer is it depends.
For hard skills generally for every job you will need to know linux, bash, and version control (usually git). Data analysis jobs generally prefer an interpreted language (Python and/or R). Software dev jobs will look for proficiency in a compiled statically typed language like C++ or Rust. More jobs want experience in pipeline development in nextflow or snakemake. Most companies like to see proficiency with an HPC or AWS/GCP. Also having knowledge of SQL, SQL-like, and NoSQL databases on these services or in general will give you a leg up.
As for general domain knowledge, depending on what job you look for they may lean more into algorithms, machine learning, statistics, or pure biological knowledge. The job will generally be tailored to a certain discipline in computational biology too, like proteomics, transcriptomics, genomics, etc. There are also differing sequencing modalities that may be more important to know based on the job like Illumina, Nanopore, PacBio, etc.
For soft skills you will be collaborating a lot in industry, so ability to communicate to general audiences is really important. You would be surprised at how many brilliant computational biologists fumble because they can't explain their work to an audience of bench scientists. It's also important to show projects that you have "delivered" on, since most companies will judge you based on their timely completion.