If you’ve ever worked as part of a data engineering team, you’ve likely noticed how data engineers are constantly juggling multiple responsibilities. On one side, we focus on building transformation…

Data Engineer Things

Delta Live Pipelines (DLT) simplify data engineering by automating infrastructure management, data quality checks, and monitoring while allowing developers to focus on transformation logic using SQL or Python. The framework supports both streaming and batch workloads through a declarative approach, handling common tasks like incremental data loading and SCD model creation. DLT pipelines can be created via code or Databricks UI, implementing medallion architecture patterns with built-in features for data lineage, quality reporting, and performance optimization.

Delta Live Pipelines Explained: Concepts to Implementation

Creating a Delta Live Table (DLT) Pipeline in Databricks

Scenario: Customer Data Pipeline Using Delta Live Tables