Why AI Agents Are Creating a New Kind of Data Engineer
Why the rise of AI agents is creating Intelligence engineers
As per the Gartner 2024 survey 62% of organizations using AI-driven orchestration saw 40% or greater reduction in pipeline maintenance time.The figure is not a forecast but it is actually happening. To understand this advent we will trace back how data engineering reached here.
Data Engineering began in the Manual ETL where everything was hand built using tools such as Informatica,DataStage,custom python/SQL jobs and on-premise Oracle.Pipelines required a specialist to maintain them.
The cloud native era changed the infrastructure equation.Workloads migrated to Redshift,Snowflake,Apache Spark, and Airflow,abstracting server management away from engineering team.But significant effort still remained - pipeline logic,orchestration design, and data quality were all manually executed.Finally the modern data stack era which democratized pipeline building utilizing tools such as dbt,airbyte,databricks along with the rise of analytics engineer as a critical role but keeping monitoring,debugging,incident response on the engineering team.
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