Snowflake Engineer

Key Responsibilities

• Core Snowflake Administration: Manage all aspects of the Snowflake environment, including user provisioning, role-based access control (RBAC), and security policies.
• Performance & Cost Management: Proactively monitor and optimize virtual warehouses, query performance, and storage to ensure platform efficiency and cost-effectiveness.
• Data Pipeline & Ingestion: Oversee, manage, and monitor data ingestion processes into Snowflake from various sources, ensuring reliability and data integrity.
• dbt Model Development: Create, maintain, and modify dbt models to support data transformation, business logic, and reporting needs within our pipelines.
• Database Management: Handle the creation and maintenance of databases, schemas, views, and other objects.
• SQL Optimization: Serve as the team's SQL expert, helping to analyze complex queries, identify bottlenecks, and recommend tuning improvements.
• Support & Troubleshooting: Act as the primary point of contact for all Snowflake-related support, access, and administrative issues.
• Continuous Improvement: Stay current with new Snowflake features and best practices. Be curious and willing to learn new technologies to help improve our data stack.

Required Skills & Qualifications

• Proven experience as a Snowflake Administrator or in a similar data warehousing role (e.g., Data Engineer, Analytics Engineer).
• Excellent SQL knowledge: Demonstrated ability to write, debug, and optimize complex SQL queries.
• Hands-on experience with dbt: Demonstrable experience creating, modifying, and maintaining dbt models.
• Solid understanding of data warehousing concepts, database architecture, and modern ELT processes.
• Experience with core admin tasks: user management, security (RBAC), and resource monitoring.
• A strong sense of ownership and the ability to work independently, manage priorities, and take initiative on a lean team.
• Excellent problem-solving and communication skills.

Preferred Qualifications 

• SnowPro Core Certification
• Python Knowledge: Familiarity with Python for scripting, UDFs, or Snowpark. (Experience with the Python 3.10 or 3.11 runtimes is a significant plus).
• Experience with data integration tools (e.g., Qlik Replicate,Airbyte).
• Familiarity with a major cloud platform (AWS, Azure, or GCP).

Others:

• Language requirements: Proficiency in Mandarin and English
• Good ability of Project management, PMP certificate is a plus
• Minimum of 5 years of experience in data analytics, business intelligence, and data engineering roles
• Experience in data visualization tools like as Qlik