To excel as a Data Linguist, you need a solid background in linguistics, computational linguistics, or a related field, combined with strong analytical and data annotation skills. Familiarity with tools such as Python, NLP frameworks (like spaCy or NLTK), and annotation platforms is commonly required. Excellent attention to detail, collaboration skills, and the ability to communicate complex language patterns clearly can set you apart. These competencies are crucial for accurately structuring, processing, and interpreting language data in support of various computational projects.