Employer description & source details
Extensive hands-on experience in Snowflake architecture, data platform engineering, and enterprise data solution design. Strong expertise in Snowflake account, warehouse, database, and schema design, including multi-cluster warehouses and multi-environment strategies. Advanced SQL skills, including complex queries, stored procedures, incremental processing, query profiling, and performance optimization. Strong Python programming skills for data processing, API integration, automation, and Snowflake development using Snowpark and libraries such as pandas. Working knowledge of SQL Server, including database concepts, SQL querying, and integration with enterprise data platforms. Hands-on experience with Azure Data Factory for data ingestion, orchestration, and integration workflows. Strong knowledge of Snowflake Dynamic Tables, Streams, Tasks, Snowpark, semantic views and models, Secure Data Sharing, cloning, Time Travel, replication, and failover. Proven experience with Snowflake governance capabilities, including RBAC, masking policies, row access policies, object tagging, tag-based masking, data classification, data quality monitoring functions (DMFs), Access History, and Object Dependencies. Strong understanding of dimensional modeling, Data Vault, hybrid modeling, and layered or medallion architecture patterns. Experience defining canonical keys, managing loosely typed source data, implementing deduplication, and preventing join fanout across related business domains. Expertise in ETL/ELT architecture and data pipeline development, with familiarity with dbt, Airflow, dbt Cloud, or native Snowflake Tasks. Experience integrating Salesforce CRM, market data feeds, third-party data sources, APIs, files, and streaming data into Snowflake. Understanding of Commercial Real E
Extracted skills: python, sql, postgresql, azure, docker, terraform, machine learning, power bi, tableau, sales, security