Snowflake Data Engineer

Cognitive Engineering Key Responsibilities: Snowflake Architecture & Engineering: • Lead and implement Snowflake solutions across data ingestion, storage, transformation, and access. • Lead end-to-end implementation of solutions using Snowflake’s latest features. • Develop reusable frameworks, UDFs, and components using Snowpark or SQL scripting. • Develop performance-optimized pipelines using Snowflake-native capabilities and modern ELT tools. • Establish data governance, security models, RBAC, and masking policies in line with compliance standards. • Conduct performance tuning, workload monitoring, and optimization. GenAI: • Enable GenAI use cases leveraging Snowflake’s native capabilities • Implement Cortex AI features with custom workflows and business logic • Required Qualifications and Certifications: • 8+ years of experience as a Snowflake Lead or Data Engineer. • Good command of Snowflake internals, including performance tuning, clustering, caching. • Good Knowledge of SQL, Snowflake scripting, and at least any one cloud platforms (AWS, Azure, or GCP). • Knowledge of Advanced Features like dynamic tables, Snow pipe streaming, Snowflake Cortex AI etc. • Good communication skills with the ability to bridge technical and business discussions. • Certifications: SnowPro Core Certified. Minimum 2 year(s) of experience is required

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