Employer description & source details
Strong experience in data architecture, data engineering, or enterprise data platforms, with substantial hands-on experience in Snowflake. Strong expertise in Technology Architecture and Data Architecture, including solution design, data modeling, integration, and implementation of scalable enterprise platforms. Strong hands-on experience with Snowflake security, data governance frameworks, access management, and compliance controls. Proficiency in Snowflake Row Access Policies (RAP), Role-Based Access Control (RBAC), role hierarchies, least-privilege permissions, dynamic data masking, and tag-based masking policies. Experience enforcing access controls at database, schema, object, row, and column levels. Strong understanding of data ownership, stewardship, classification, metadata management, data lineage, data quality, and audit requirements. Strong SQL skills, including complex queries, stored procedures, incremental processing, and query performance tuning. Strong Python programming skills for data processing, API integration, automation, and pipeline development. Experience with PostgreSQL and enterprise database architecture, including data modeling, integration, and performance optimization. Hands-on experience with Streamlit application development and Snowflake Cortex capabilities, including Cortex Analyst, Cortex Search, Cortex Agents, and semantic modeling. Ability to evaluate AI-generated responses and implement appropriate security and governance controls for AI applications. Experience building and managing data ingestion and transformation pipelines using Azure Data Factory, AWS Glue, Python, or equivalent tools. Strong understanding of full loads, incremental loads, CDC, data validation, error handling, and pipeline monitoring. Familiarity with AWS servi
Extracted skills: python, sql, postgresql, aws, azure, security