Design and Develop scalable and efficient data models in Snowflake for various business needs.
Create and maintain ETL/ELT pipelines using Snowflake and other integration tools (e.g., Python, SQL, and third-party data tools like Apache Airflow, dbt).
Write optimized SQL queries for data extraction, transformation, and loading (ETL/ELT) to ensure high performance and scalability.
Implement Snowflake features such as micro-partitioning, clustering, and time travel to optimize data processing and querying.
Work closely with data analysts, data scientists, and business stakeholders to understand their data needs and translate them into actionable Snowflake solutions.
Manage Snowflake account configurations, including databases, schemas, warehouses, and roles.
Monitor and troubleshoot data pipeline issues, improving system reliability and performance.
Create automated scripts for data integration and workflow management in Snowflake.
Ensure data security and compliance by adhering to best practices in Snowflake data governance and access management.
Develop and maintain documentation for Snowflake data models, ETL pipelines, and processes.

Strong hands-on experience with Snowflake development, including working with data warehouses, databases, and Snowflake-specific features (e.g., stages, pipes, tasks, and streams).
Proficiency in SQL and experience with performance tuning for large datasets.
Experience with ETL/ELT processes and tools (e.g., Apache Airflow, dbt, Talend, Informatica).
Familiarity with data integration tools and programming languages (e.g., Python, Spark, or Scala).
Understanding of data modeling principles (star schema, snowflake schema, normalized vs. denormalized).
Knowledge of cloud platforms (AWS, Azure, or GCP) and their integration with Snowflake.
Experience with data security and compliance in Snowflake (role-based access control, encryption, etc.).
Strong problem-solving, troubleshooting, and optimization skills.