Does a data science project really need a dedicated data engineer, or can a skilled data scientist handle the pipeline work themselves? I've seen startups where one person does both and things move fast, but also enterprise teams where poor data infrastructure causes constant model failures. Having spent six years in analytics roles, I lean toward hiring specialists once your data volume crosses ten terabytes.