Sr. Data Engineer

Qualifications:
10 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.