Skillset and Responsibilities Comparison:

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I have experienced each of these roles at a variety of different organizations. However, every organization is unique and the data landscape creates a new branch of knowledge every few months. With that said, please take this information from the perspective of one individual. Everyone’s experience will be different.

Data Analyst

Analysts will be the closest individuals to actionable data. They should have a pulse on the business, team, department etc. A good analyst will be embedded into their stakeholders work. The job of an analyst should not only be to report what they’re seeing but instead, report and recommend further action.

An analyst will spend most of their time querying data, usually using SQL, building visual reports for stakeholders, presenting their findings and lastly recommending next step action items to their stakeholders.

Analytics Engineer

Some might say an analytics engineer is nothing but a SQL monkey but that shouldn't be the case. This type of engineer should also have a deep understanding of why and how the business rules were curated. Misinterpreting business rules will lead to disastrous, unusable data models.

In defense of the SQL monkey, an Analytics Engineer should also be ingrained in the team they are supporting. Otherwise, you end up with a product that may meet the requirements but does not fulfill the business need.

Data Engineer

As with the previous two roles, a Data Engineer can take a variety of forms. A DE may be responsible for solely data modeling or heavy on ingestion and pipeline infrastructure. Whichever end of the spectrum, a DE will be a jack of all data trades. They will write SQL in their sleep and should also be able to spin and tear down data resources in the cloud.

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Disclaimer: These are not black and white! As you’ve seen under other possible titles, these roles have a lot of overlap. Also, in a smaller organization, I would expect to find one individual doing all three of these functions.