Key skills
AWSCloudERPETLPythonSQLAIMLAgenticELTData EngineeringSnowflakeLambdaS3IAMGlueRemote Work
About this role
Role Overview
- Design and maintain scalable data pipelines.
- Structure, transform, and optimize data in Snowflake.
- Implement multi-source ETL/ELT flows (ERP, APIs, files).
- Leverage the AWS environment, including S3, IAM, and various data services.
- Prepare data for Data Science teams and integrate AI/ML models into production.
- Ensure data quality, security, and governance.
- Provide input on data architecture.
Requirements
- 5+ years of experience in data engineering, including significant experience in a cloud environment.
- Snowflake (MUST HAVE): Expertise in modeling, query optimization, cost management, and security.
- AWS: Strong knowledge of data and cloud services including S3, IAM, Glue, and Lambda.
- Languages: Advanced SQL and Python for data manipulation, automation, and ML integration.
- Data Engineering: Proven experience in ETL/ELT pipeline design.
- AI/ML Integration: Ability to prepare data for model training and deploy AI models into production workflows (batch or real-time).
- Nice to Have: Experience with agentic AI architectures, including agent orchestration and decision loops.
- Integration of agent-driven AI models into existing data pipelines.
- Knowledge of modern architectures such as Lakehouse or Data Mesh.
Tech Stack
- AWS
- Cloud
- ERP
- ETL
- Python
- SQL
Benefits
- Remote work options