Data engineers commonly need to transform large volumes of data. Apache Spark pools in Azure Synapse Analytics provide a distributed processing platform that they can use to accomplish this goal.

Learn how to build real-time data ingestion pipelines using Apache Kafka.

In most organizations, a data engineer is the primary role responsible for integrating, transforming, and consolidating data from various structured and unstructured data systems into structures that are suitable for building analytics solutions. An Azure data engineer also helps ensure that data pipelines and data stores are high-performing, efficient, organized, and reliable, given a specific set of business requirements and constraints.

Learn techniques for automating data pipelines for faster data processing.

Microsoft Azure provides a comprehensive platform for data engineering; but what is data engineering? Complete this module to find out.

Apache Spark is a highly scalable distributed processing solution for big data analytics and transformation. You can leverage its power in Azure Synapse Analytics by using Spark pools.