AI Data Engineer – ML Data Pipelines

This is a fully remote position, open to applicants in United States.

📋 Description

• Create and develop scalable data pipelines for machine learning workflows.

• Design processes for feature engineering and data preparation.

• Implement systems for both batch and real-time data ingestion.

• Ensure the quality, validation, and monitoring of data.

• Collaborate with machine learning engineers to facilitate model training and deployment.

• Integrate data pipelines with orchestration tools such as Airflow or similar.

• Enhance pipeline performance and optimize cloud cost efficiency.

• Maintain comprehensive documentation and version control for data workflows.

⛳️ Requirements

• Minimum of 4 years of experience in Data Engineering.

• Proficient in Python and SQL.

• Experience in building data pipelines for machine learning or analytics applications.

• Practical experience with Spark, Databricks, or comparable distributed processing frameworks.

• Familiarity with orchestration tools like Airflow or similar.

• Experience working in AWS, Azure, or GCP environments.

• Knowledge of data quality validation and monitoring frameworks.

• Understanding of feature engineering and the data lifecycle for models.

🏝️ Benefits

• Opportunities for remote work.