Which of the following is a primary responsibility of a data engineer working with Databricks?

Developing data pipelines is a primary responsibility of a data engineer working with Databricks. Data engineers focus on designing, constructing, and maintaining robust data pipelines that facilitate the collection, transformation, storage, and processing of data. This involves utilizing Databricks to implement ETL (Extract, Transform, Load) processes, employing Spark for large-scale data processing, and ensuring data integrity and quality throughout these workflows.

In addition to constructing pipelines, data engineers also consider performance optimization, data schema design, and implementing best practices for data governance. By efficiently managing this flow of data, data engineers enable data teams to access reliable and relevant datasets for analysis and reporting, ultimately contributing to informed decision-making within the organization. The emphasis is on the technical aspects of data management, which distinguishes this responsibility from other roles like data visualization or analysis.