The 27 Best AI Agents for Data Engineering to Consider in 2025

By Solutions Review Executive Editor Tim King

The proliferation of generative AI has ushered in a new era of intelligent automation, with AI agents at the forefront of this transformation. From code-writing copilots to pipeline orchestration assistants, these tools are reshaping how data teams design, maintain, and scale their infrastructure. This guide breaks down the top AI agents and platforms for data engineering in 2025, categorized to help you find the right tool for your needs.

Key Categories and Tools

Data Pipeline Automation and Orchestration

1. Apache Airflow
   Use For: Authoring and scheduling complex, dependency-aware data workflows.
   Key Features: Python-based DAGs, extensible with community operators, centralized UI for monitoring.
   Get Started: Ideal for batch processing, data warehouse jobs, or ML model orchestration.

2. Prefect
   Use For: Modern, Pythonic orchestration with better observability.
   Key Features: Python-native workflows, cloud monitoring, dynamic workflows.
   Get Started: Perfect for fast-moving teams valuing observability and clean code.

3. Luigi
   Use For: Lightweight orchestration of batch data workflows.
   Key Features: Python classes for tasks, dependency resolution, simple web UI.
   Get Started: Best for smaller workflows or development environments.

4. Mage AI
   Use For: Notebook-style pipeline building with AI-powered suggestions.
   Key Features: Support for Python, SQL, and R, real-time pipeline execution.
   Get Started: Ideal for fast-moving analytics environments.

5. Dagster
   Use For: Asset-centric orchestration with strong data lineage.
   Key Features: Declarative pipeline definitions, automatic lineage tracking.
   Get Started: Best for environments prioritizing lineage and quality.

6. CrewAI
   Use For: Coordinating multiple specialized AI agents.
   Key Features: Multi-agent collaboration, integration with LLMs.
   Get Started: Great for innovation labs or agent-based system exploration.

How This List Was Compiled

This list was generated through web research using advanced scraping techniques and generative AI tools. Solutions Review editors employed a multi-prompt approach to optimize content for relevance and utility, supplemented by their weekly news distribution services.

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