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Data engineer

As explained in The Art of AI Product Development

A data engineer is a practitioner who builds and operates systems and processes for collecting, transforming, governing, and providing access to data.

A data engineer builds and operates processes and systems that process data, monitor its quality, and manage access for stakeholders. section 12.1.2

Core responsibilities include:

  • Implement data-processing systems and workflows. section 12.1.2
  • Monitor data quality and grant or manage stakeholder access. section 12.1.2
  • Prepare unstructured text and image data through sophisticated pipelines for generative AI training and inference. section 12.1.2

How The Art of AI Product Development covers it

How deep it goes
Explains core responsibilities and rising importance for unstructured generative AI data, but does not detail implementation methods.
What you can do after
Operate data-processing systems, monitor data quality, and manage data access for key stakeholders.
How it connects
Distinguishes data engineering from AI engineering, machine learning engineering, MLOps engineering, and prompt engineering.

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This explainer was generated by Manning's knowledge graph from the text of The Art of AI Product Development. The section links point to the parts of the book it draws on.