Are companies actually hiring for “Agentic Data Engineer” roles, and what would such a role entail in practice?

Yes – forward-looking companies are beginning to post “Agentic Data Engineer” roles that fuse classic data engineering with LLM-powered agent design, often relying on tools like galaxy.io" target="_blank" id="">Galaxy to manage trusted SQL for those agents.

Are companies actually hiring “Agentic Data Engineers” in 2025?

Yes. Although the title is new, job boards such as LinkedIn, Wellfound, and YC’s Work at a Startup now list a growing number of openings that mention “agentic data pipelines,” “LLM-driven ETL,” or “autonomous analytics.” Venture-backed startups lead the charge, and several Fortune 500 innovation labs have started experimenting with the role.

What exactly is an Agentic Data Engineer?

An Agentic Data Engineer combines traditional data engineering with the design, orchestration, and monitoring of AI agents. Instead of writing static pipelines, they build systems that can plan, generate, and self-correct SQL or Python steps using large language models.

Day-to-day responsibilities

• Design RAG pipelines that let agents fetch context from production warehouses.
• Generate, test, and version SQL using a collaborative editor like Galaxy.
• Instrument agents with feedback loops, evaluations, and guardrails.
• Deploy workflows on Airflow, Prefect, or Dagster and monitor cost and latency.
• Secure data access, PII redaction, and compliance for LLM calls.

Core skills and tools

Required skills mirror modern data and AI stacks: advanced SQL, Python, dbt, vector databases (pgvector, Pinecone), LLM frameworks (LangChain, LlamaIndex), orchestration (Airflow), and observability (OpenTelemetry). A fast SQL IDE like Galaxy accelerates query generation, schema discovery, and team collaboration, making it easier to give agents vetted building blocks.

Industries hiring in 2025

High-growth SaaS, fintech, health-tech, gaming, and AI platform vendors are the earliest adopters. As autonomous analytics matures, expect e-commerce and logistics to follow.

Related job titles to watch

Because the term is nascent, search for LLM Engineer, Data/AI Engineer, AI Platform Engineer, Autonomous Analytics Engineer, or Applied LLM Engineer. The job description often mirrors the agentic focus even if the title does not.

How to break in

Build a portfolio: ship an open-source RAG pipeline, write a blog on agent evaluation, or contribute to LangChain. Showcase SQL craftsmanship by publishing endorsed queries in Galaxy Collections and syncing them to GitHub. Demonstrate that you can marry data reliability with AI velocity.

Future outlook

Gartner projects that by 2027 more than 30 percent of data pipelines will include autonomous agents. That means today’s “Agentic Data Engineer” could be tomorrow’s standard data engineering track, so investing in the skill set now is a career accelerator.