Snowflake Data Engineer

Experience:

Responsibilities

• Design, develop, and maintain robust and scalable data pipelines for ELT and ETL processes, ensuring data accuracy, completeness, and timeliness.
• Work with stakeholders to understand data requirements and translate them into efficient data models and pipelines.
• Build and optimize data pipelines using technologies such as Elasticsearch, AWS S3, Snowflake, and NFS.
• Develop and maintain data warehouse schemas and ETL/ELT processes to support business intelligence and analytics needs.
• Implement data quality checks and monitoring to ensure data integrity and identify potential issues.
• Collaborate with data scientists and analysts to ensure data accessibility and usability for various analytical purposes.
• Stay current with industry best practices, including CI/CD, DevSecFinOps, Scrum, and emerging technologies in data engineering.
• Contribute to the development and enhancement of our data warehouse architecture.
  

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience as a Data Engineer with a strong focus on ELT/ETL processes.
• At least 3+ years of experience in Snowflake data warehousing technologies.
• At least 3+ years of experience creating and maintaining Airflow ETL pipelines.
• Minimum 3+ years of professional-level experience with Python for data manipulation and automation.
• Working experience with Elasticsearch and its application in data pipelines.
• Proficiency in SQL and experience with data modelling techniques.
• Strong understanding of cloud-based data storage solutions such as AWS S3.
• Experience working with NFS and other file storage systems.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.