Snowflake Developer - Data Engineering

What You'll Do :

• Snowflake Development : Design, develop, and implement robust, scalable, and high-performance data warehousing solutions on the Snowflake cloud data platform.
• ETL / ELT Pipeline Construction : Build and maintain efficient ETL / ELT (Extract, Transform, Load / Extract, Load, Transform) processes utilizing Snowflake features such as Snowpipe, Tasks, Streams, and stored procedures.
• SQL Expertise : Write and optimize complex SQL queries for data extraction, transformation, loading, and analysis within Snowflake.
• Data Modeling : Contribute to and implement dimensional and relational data models optimized for analytical reporting and performance on Snowflake.
• Performance Tuning & Cost Optimization : Proactively identify and resolve performance bottlenecks within Snowflake, and optimize resource utilization to manage costs effectively.
• Data Integration : Integrate Snowflake with various data sources (e.g., cloud storage, databases, APIs) and downstream applications (e.g., BI tools, data visualization platforms).
• Data Governance & Security : Implement and maintain data governance, security, and access control policies within Snowflake.
• Collaboration : Work closely with data architects, data scientists, business intelligence analysts, and business stakeholders to understand requirements and deliver data solutions.
• Automation : Develop scripts (e.g., Python, Shell) for automation of data processes, monitoring, and administrative Skills & Qualifications :
• Experience : 5+ years of professional experience in data warehousing and data engineering, with a strong focus on cloud data platforms.
• Snowflake Expertise : Deep understanding and hands-on experience with the Snowflake cloud data platform, including its architecture, key features (Virtual Warehouses, Zero-Copy Clones, Time Travel, Caching), and best practices.
• SQL Proficiency : Expert-level proficiency in SQL for data manipulation, querying, and optimization.
• ETL / ELT Methodologies : Proven experience in designing and implementing ETL / ELT processes and data pipelines.
• Data Modeling : Strong understanding of data warehousing concepts and data modeling techniques (e.g., dimensional modeling, 3NF).
• Scripting : Experience with scripting languages such as Python or Shell for data processing and automation.
• Version Control : Proficient in using Git for version control and collaborative development.
• Problem-Solving : Strong analytical and problem-solving skills, with the ability to troubleshoot complex data-related issues.
• Communication : Excellent verbal and written communication skills to articulate technical concepts and collaborate effectively with diverse teams.

Preferred Skills (Nice-to-Have) :

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