Description

You will design, build, and optimize data pipelines, machine learning models, and analytics solutions.

This role is on-site.

Responsibilities

• Develop and maintain ETL pipelines using AWS Glue for data ingestion, transformation, and integration.
• Utilize Python and Spark for data preprocessing, feature engineering, and model development.
• Design and implement data lake architecture using Snowflake Data Lake, Snowflake data warehouse, and S3.
• Leverage SageMaker for model training, evaluation, deployment, and monitoring in production.
• Conduct exploratory data analysis and data visualization to communicate findings and trends.

Required Skills

• 6+ years of professional experience in data engineering or data science roles.
• Proficiency in Python and Spark for data processing.
• Experience with AWS Glue for ETL pipeline development.
• Hands-on work with Snowflake Data Lake and S3.
• Experience using SageMaker for machine learning lifecycles.
• Strong knowledge of SQL and NoSQL databases.
• Bachelor's degree.

Key Skills

Education

Bachelor's degree