Snowflake Architect

Qualifications7+ years of experience in data engineering with strong hands-on expertise in Snowflake and Power BI Proven ability to design analytics-ready data models and enterprise BI solutions Deep understanding of ELT/ETL patterns, data warehousing concepts, and performance tuning Strong experience in Snowflake architecture design, including multi-cluster warehouses, workload isolation, and scaling strategies Expertise in designing layered data architectures (Bronze/Silver/Gold or Medallion) within Snowflake Hands-on experience with Snowflake features such as Snowpipe, Streams, Tasks, Time Travel, and Zero-Copy Cloning Strong knowledge of micro-partitioning, clustering, and pruning optimization for large-scale datasets Experience implementing data governance, RBAC, masking policies, row-level security, and secure data sharing in Snowflake Proven ability to optimize query performance and manage cost efficiency using warehouse sizing, caching, and query tuning techniques Experience with Snowflake Cortex / AI & "super intelligence" capabilities for enabling AI-driven data applications, including use of built-in LLM functions, vectorized data access, and intelligent data enrichment Familiarity with Snowpark and Snowflake-native application development for advanced data processing and ML workloads Exposure to Snowflake Native Apps / Snowlit (Snowflake app framework) for building and deploying data applications within the Snowflake ecosystem Understanding of unstructured data handling and AI/ML integrations within Snowflake (e.g., document processing, embeddings, vector search) Experience building and optimizing Power BI dashboards, semantic models, and DAX calculations Proficiency in SQL and Python for data transformation and automation Experience with Azure Data Factory and cloud-based data ecosystems Ability to translate business requirements into scalable data models and actionable insights