Snowflake Data Warehouse Engineer
Qualifications & Certifications:
- Bachelor's Degree in any relevant field
- At least 2 years of experience in data engineering and data warehousing (Snowflake Lead or Data Engineer.)
- Internal Mastery: Expert-level command of Snowflake internals, including micro-partitioning, caching mechanisms, and clustering.
- Technical Skills: Strong proficiency in SQL, Snowflake scripting, and at least one major cloud platform (AWS, Azure, or GCP).
- Advanced Knowledge: Hands-on experience with Snowpark, Cortex AI, and Snowflake's modern ELT/Data Engineering features.
- SnowPro Core Certified
Key Responsibilities:
- Solution Leadership: Lead the end-to-end implementation of Snowflake solutions, covering ingestion, storage, transformation, and data access.
- Pipeline Development: Build performance-optimized, reusable frameworks and pipelines using Snowflake-native capabilities, Snowpark, and modern ELT tools.
- Governance & Security: Establish enterprise-grade data governance, including RBAC (Role-Based Access Control), security models, and data masking policies.
- Performance Engineering: Conduct deep-dive performance tuning, clustering, and workload monitoring to ensure cost-efficient operations.
- AI Integration: Enable GenAI use cases by implementing Snowflake Cortex AI features with custom workflows and business logic.
- Modern Features: Deploy advanced functionalities such as Dynamic Tables and Snowpipe Streaming to ensure real-time data availability.
