The Data Analyst is the person who turns a company's data into concrete answers to business questions: why sales are dropping in a region, which acquisition channel pays off most, where users drop out of the journey.
Their daily work: extracting and combining data in SQL, cleaning it, building dashboards (Looker, Power BI, Tableau, Metabase), then presenting conclusions to product, marketing, finance or leadership teams. They also use Python or an advanced spreadsheet for one-off analyses.
They sit between the Data Engineer, who builds and secures data flows upstream, and the Data Scientist, who designs predictive models. In small teams, the boundaries are blurry and the Analyst often handles part of the data modeling, a role sometimes called Analytics Engineer when it relies on dbt.
Why it matters when hiring
The Data Analyst is often the first data hire for a company that wants to steer by numbers, provided the data is already accessible. The strong signal on a resume: analyses that changed a decision, not just dashboards delivered. In an interview, test SQL on a real case and ask them to explain a result to a non-technical person.