Data Engineer – A builder. Sets up, tests and maintains the infrastructure that Data Scientists use to carry out their work.
Data Analyst – Studies historical data to generate insights into a company’s performance. Typically strong with popular visualisation tools such as Tableau, SQL and Python / R. Advanced analysts may have a background in statistics.
Data Scientist – Combines the roles above, applying machine learning techniques to power a forward-looking, predictive approach. A good Data Scientist will be a strong communicator, conveying their findings to audiences at all levels of the business.