Description

Design and maintain scalable data pipelines and warehousing solutions on AWS and Snowflake. You will own the end-to-end implementation of ETL/ELT processes, ensuring data integrity and performance.

Responsibilities

• Build and optimize data pipelines using PySpark, Python, and SQL within AWS EMR, EC2, and S3.
• Design and implement dimensional data models (star/snowflake schemas) and semantic models in Snowflake.
• Develop and manage transformation logic using dbt and orchestrate workflows with Apache Airflow.
• Implement data governance standards, including encryption, masking, and role-based access control.
• Collaborate with data scientists and analysts to translate business requirements into technical solutions.

Required Skills

• 10+ years of experience as a Data Engineer or in similar data-focused roles.
• Proficiency in SQL, Python, and PySpark for data manipulation and processing.
• Hands-on expertise with AWS services: S3, EMR, EC2, and Airflow.
• Deep knowledge of Snowflake for data warehousing and management.
• Experience with dbt for data transformation and testing.
• Strong understanding of data modeling concepts and best practices.
• Proficient with Git for version control and collaboration.

Preferred Skills

• Experience mentoring junior team members and guiding technical deliverables.
• Familiarity with Agile ceremonies and cross-functional coordination.

Key Skills

Education

Bachelor's degree