Understanding and using data science programming languages other than Python will become more critical as the field continues to become more granular and information-heavy. Julia, Scala, Go, Rust, and SAS all provide specific capabilities to solve unique data-centric problems, whether that means high-performance computing or enterprise analytics.
Being able to program across a variety of different programming languages in this context brings more flexibility and creativity, and less constraint, to data professionals and leads them well into the future of the industry.