Job Summary:
We are seeking a Snowflake Engineer to design, build, and optimize scalable data solutions using the Snowflake Data Cloud. The ideal candidate will have strong expertise in data modeling, ELT/ETL pipelines, SQL performance tuning, and cloud integration, enabling robust and efficient data processing for analytics and business insights.
Key Responsibilities:
Design, develop, and maintain data pipelines and data models in Snowflake.
Implement data ingestion, transformation, and integration processes from multiple structured and unstructured data sources.
Optimize Snowflake performance through clustering, partitioning, caching, and query tuning.
Build secure and efficient data sharing and data governance frameworks within Snowflake.
Collaborate with analytics, BI, and data science teams to deliver high-quality datasets and data marts.
Integrate Snowflake with ETL/ELT tools (Informatica, dbt, Matillion, Talend, etc.) and orchestration tools (Airflow, Azure Data Factory, AWS Glue).
Implement role-based access control (RBAC), data masking, and other security mechanisms.
Automate monitoring and management of data pipelines and ensure data quality and reliability.
Stay updated with Snowflake's latest features, releases, and best practices. Technical Skills:
Core Expertise: Snowflake Data Warehouse (architecture, performance tuning, best practices)
Data Modeling: Dimensional modeling (Star/Snowflake schema), normalization/denormalization
SQL Expertise: Advanced SQL scripting, query optimization, stored procedures, and UDFs
ETL/ELT Tools: dbt, Informatica, Talend, Matillion, Apache Airflow, Azure Data Factory, or AWS Glue
Programming Languages: Python, SQL, or Java (for automation and integrations)
Cloud Platforms: AWS, Azure, or GCP (with Snowflake integration)
Version Control: Git, CI/CD pipelines (Jenkins, GitLab CI/CD)
Optional (Nice-to-Have):
Knowledge of Snowpark, Streamlit, or Snowflake Native Apps
Experience with data lakes, Kafka, or real-time data streaming
Familiarity with Power BI, Tableau, or Looker Soft Skills:
Strong analytical and problem-solving skills
Ability to work collaboratively with cross-functional teams
Strong communication and documentation skills
Detail-oriented with focus on data accuracy and reliability