Responsibilities

• Design, develop, and implement solutions using core Snowflake features such as SnowSQL, Snowpipe, Tasks, Streams, Time Travel, Zero-Copy Cloning, Stored Procedures, Metadata Manager, Optimizer, and Data Sharing.
• Build and maintain ETL/ELT pipelines leveraging Databricks, Python, and SnowSQL for ingestion and transformation of structured and semi-structured data.
• Develop scripts using Python, Unix Shell, and other tools to support data extraction, transformation, loading, and utility functions.
• Apply best practices in data modeling (OLTP, OLAP), including design and implementation of dimensions, facts, and other data warehouse components.
• Collaborate with teams to configure and optimize Snowflake on Microsoft Azure, with a solid understanding of Azure-specific configurations related to Snowflake.
• Provide production support for Snowflake-based data solutions, addressing issues such as data load failures, performance bottlenecks, and transformation errors.
• Translate business and technical requirements into scalable data transformation logic, ensuring solutions are robust, maintainable, and well-documented.
• Review and optimize existing code and data models to ensure alignment with standards, performance benchmarks, and architectural best practices.
• Implement automated testing strategies (e.g., cloud-based testing frameworks) and maintain clear documentation for data pipelines, transformations, and deployments.
• Contribute to solution architecture design, including integration with external data processing, storage, and reporting tools.

Requirements

• 8+ years of experience in designing, developing, and deploying large-scale, production-grade data solutions on Snowflake Data Warehouse on Microsoft Azure.
• Proven hands-on experience with Snowflake, including SnowSQL, Snowpipe, Streams, and other advanced features.
• Strong proficiency in Python and Databricks for building scalable data ingestion and transformation pipelines.
• Deep understanding of Snowflake internals, performance tuning, and integration with BI/reporting and data processing tools.
• Strong grasp of data warehouse architecture, including dimensional modeling, data governance, and security best practices.
• Familiarity with Azure services and configurations in the context of Snowflake integration.
• Excellent analytical, problem-solving, and communication skills—both verbal and written—with the ability to navigate ambiguity and drive clarity in solution design.

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