Snowflake Developer
Key Responsibilities
Design, develop, and maintain Snowflake data warehouse solutions.
Build, test, and deploy dbt models (staging, intermediate, marts).
Implement SQL-based ELT pipelines using dbt best practices (modularity, documentation, testing).
Optimize Snowflake performance (clustering, micro-partitioning, query tuning).
Create and manage Snowflake roles, warehouses, schemas, and data-sharing configurations.
Collaborate with data engineers, analysts, and business teams to define data models and transformations.
Maintain version control (Git) and CI/CD workflows for dbt deployments.
Ensure data quality through dbt tests, data validation, and monitoring.
Write efficient, scalable SQL for complex transformations.
Develop and maintain documentation for data models, pipelines, and architecture.
Skill Requirements
Strong SQL expertise.
Hands-on experience with Snowflake (warehouses, stages, streams, tasks, performance tuning).
Proficiency in dbt Core or dbt Cloud.
Experience with Git, CI/CD, and modern data stack tools.
Familiarity with ETL/ELT concepts and data modeling (e.g., Kimball, star schema).
Optional but valuable: Airflow, Python, cloud platforms (AWS/Azure/GCP).
Design, develop, and maintain Snowflake data warehouse solutions.
Build, test, and deploy dbt models (staging, intermediate, marts).
Implement SQL-based ELT pipelines using dbt best practices (modularity, documentation, testing).
Optimize Snowflake performance (clustering, micro-partitioning, query tuning).
Create and manage Snowflake roles, warehouses, schemas, and data-sharing configurations.
Collaborate with data engineers, analysts, and business teams to define data models and transformations.
Maintain version control (Git) and CI/CD workflows for dbt deployments.
Ensure data quality through dbt tests, data validation, and monitoring.
Write efficient, scalable SQL for complex transformations.
Develop and maintain documentation for data models, pipelines, and architecture.
Skill Requirements
Strong SQL expertise.
Hands-on experience with Snowflake (warehouses, stages, streams, tasks, performance tuning).
Proficiency in dbt Core or dbt Cloud.
Experience with Git, CI/CD, and modern data stack tools.
Familiarity with ETL/ELT concepts and data modeling (e.g., Kimball, star schema).
Optional but valuable: Airflow, Python, cloud platforms (AWS/Azure/GCP).
