Skill specialists
Hire Vetted ETL Engineers for AI Pipelines
Find data engineers who design and maintain ETL and ELT pipelines that feed AI models, data warehouses, and analytics platforms with clean, reliable, on-time data.
Top matching AI talents
AI Specialization
Availability
Experience Level
Akmal
Sneha
Yash
Parker
Chukwuemeka
Adithya Prahasith
Michael Kingslin
Eli
Samuel Alejandro
Hiring guide
Why companies hire ETL experts
ETL engineers build the data pipelines that make AI possible. Clean, reliable data is the most critical input for any ML system — and ETL engineers are the people who ensure data arrives correctly, on time, and at scale.
Popular projects
- Build reliable data pipelines feeding your AI training and inference
- Set up dbt transformations in your cloud data warehouse
- Integrate third-party APIs and SaaS data sources into your stack
- Implement automated data quality checks before models train
What to look for
- Experience with modern ELT tools (dbt, Fivetran, Airbyte)
- Knowledge of pipeline orchestration (Airflow, Prefect, Dagster)
- Strong data quality and monitoring practice
Frequently asked questions
What is the difference between ETL and ELT for AI?
ETL transforms data before loading (traditional). ELT loads raw data first, then transforms in the warehouse (modern). AI companies increasingly use ELT with dbt to keep raw data accessible for model experimentation.
What tools do ETL engineers use in modern AI data stacks?
Most modern ETL engineers use Fivetran or Airbyte for ingestion, dbt for transformation, Airflow or Prefect for orchestration, and Snowflake or Databricks as the destination. This combination is now the standard data stack for AI companies.
Skill cluster
Related skills you may also need
Browse other AI skills
Ready to hire ETL talent?
Post a job — it's free