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agentic data engineering
also agentic data integration or agent-enabled data engineering or ADE
Definition of agentic data engineering
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: the use of AI agents to plan and carry out multi-step data-engineering work, such as finding sources, building and testing pipelines, checking quality, documenting lineage, and monitoring or repairing data flows
- The team used agentic data engineering to generate a pipeline, test its quality rules, and prepare the result for human review.
- Agentic data integration reduced repetitive pipeline work but kept deployment approval with the data engineer.
Origin & history
Agentic data engineering became an established label in 2026 across enterprise data platforms and AI research. Qlik used it for production tools that let specialized agents work across data quality, catalogs, products, and pipelines; IBM used the closely related term agentic data integration for agent-run pipeline creation and operations; researchers also used Agentic Data Engineering for systems in which agents iteratively improve model-training data strategies.
Editorial references
Sources & further reading
- Qlik Delivers Agentic Data Engineering in Qlik Cloud to Help Enterprises Build Trusted Data for AI↗ Qlik · 2026-10-29
- IBM advances agentic data integration from pipeline design to operations↗ IBM · 2026-10-21
- Agentic Data Engineering for LLMs: System Design and a Controlled Empirical Study↗ arXiv · 2026-10-09
Test yourself
Which of these is the meaning of agentic data engineering?
Cite this entry
"Agentic data engineering." AI Dictionary, Dadgogo, https://dadgogo.com/dictionary/agentic-data-engineering/. Accessed 30 Oct. 2026.