Description

You will build and maintain data infrastructure to support data science operations.

This role is on-site.

Responsibilities

• Design and develop data architectures to standardize and integrate data sources for the Data Science department.
• Implement and manage ETL pipelines using Airflow via AWS Managed Workflows for Apache Airflow (MWAA).
• Develop and maintain data warehouses and data lakes utilizing Snowflake, Amazon S3, and Redshift.
• Establish and enhance CI/CD pipelines and contribute to DevOps practices to streamline integration and deployment.
• Collaborate with Data Scientists and Engineers to ensure data availability, quality, and accessibility for predictive ML models.

Required Skills

• 5+ years of experience in data engineering roles.
• Strong proficiency in Python and SQL for writing scalable code.
• Expertise with data warehousing technologies: Snowflake, Amazon S3, and Redshift.
• Proven experience building and managing ETL pipelines using Airflow and AWS services.
• Solid understanding of AWS cloud architecture.
• Experience implementing CI/CD practices using tools like Jenkins or GitLab CI/CD.
• Ability to collaborate cross-functionally and manage tasks independently.

Preferred Skills

• Master's degree or higher in a STEM field, or equivalent practical experience.

Key Skills

Education

Any Graduate