Anblicks
Key Responsibilities:
Lead the
end-to-end Snowflake platform implementation , including architecture, design, data modeling, and governance. Oversee the
migration of data and pipelines from legacy platforms
to Snowflake, ensuring quality, reliability, and business continuity. Design and optimize
Snowflake-specific data models , including use of clustering keys, materialized views, Streams, and Tasks. Build and manage scalable
ELT/ETL pipelines
using modern tools and best practices. Define and implement
standards for Snowflake development , testing, and deployment, including CI/CD automation. Collaborate with cross-functional teams including data engineering, analytics, DevOps, and business stakeholders. Establish and enforce
data security , privacy, and governance policies using Snowflake's native capabilities. Monitor and tune system performance and
cost efficiency
through appropriate warehouse sizing and usage patterns. Lead code reviews, technical mentoring, and documentation for Snowflake-related processes. Required Snowflake Expertise:
Snowflake Architecture
- Deep understanding of virtual warehouses, data sharing, multi-cluster, zero-copy cloning. Ability to enhance architecture and implement solutions as per the architecture. Performance Optimization
- Proficient in tuning queries, clustering, caching, and workload management. Data Engineering
- Experience with processing batch, real time using multiple Snowflake features like Snowpipe, Streams & Tasks, stored procedures, and data ingestion patterns. Data Security & Governance
- Strong experience with RBAC, dynamic data masking, row-level security, and tagging. Experience enabling such capabilities in Snowflake and at least one enterprise product solution. Advanced SQL
- Expertise writing, analyzing, performance optimization of complex SQL queries, transformations, semi-structured data handling (JSON, XML).
Cloud Integration
- Experience with at least one of the major cloud platforms (AWS/GCP/Azure) and services like S3, Lambda, Step Functions, etc.
end-to-end Snowflake platform implementation , including architecture, design, data modeling, and governance. Oversee the
migration of data and pipelines from legacy platforms
to Snowflake, ensuring quality, reliability, and business continuity. Design and optimize
Snowflake-specific data models , including use of clustering keys, materialized views, Streams, and Tasks. Build and manage scalable
ELT/ETL pipelines
using modern tools and best practices. Define and implement
standards for Snowflake development , testing, and deployment, including CI/CD automation. Collaborate with cross-functional teams including data engineering, analytics, DevOps, and business stakeholders. Establish and enforce
data security , privacy, and governance policies using Snowflake's native capabilities. Monitor and tune system performance and
cost efficiency
through appropriate warehouse sizing and usage patterns. Lead code reviews, technical mentoring, and documentation for Snowflake-related processes. Required Snowflake Expertise:
Snowflake Architecture
- Deep understanding of virtual warehouses, data sharing, multi-cluster, zero-copy cloning. Ability to enhance architecture and implement solutions as per the architecture. Performance Optimization
- Proficient in tuning queries, clustering, caching, and workload management. Data Engineering
- Experience with processing batch, real time using multiple Snowflake features like Snowpipe, Streams & Tasks, stored procedures, and data ingestion patterns. Data Security & Governance
- Strong experience with RBAC, dynamic data masking, row-level security, and tagging. Experience enabling such capabilities in Snowflake and at least one enterprise product solution. Advanced SQL
- Expertise writing, analyzing, performance optimization of complex SQL queries, transformations, semi-structured data handling (JSON, XML).
Cloud Integration
- Experience with at least one of the major cloud platforms (AWS/GCP/Azure) and services like S3, Lambda, Step Functions, etc.