Snowflake Data Architect
Job Summary
Job Description
This role requires a Snowflake Data Architect to contribute to and lead the development of Enterprise Data and Analytics Platforms. Responsibilities include expanding, optimizing, and monitoring data pipelines; implementing enterprise data warehouse solutions with Snowflake; developing project requirements for end-to-end ETL; improving existing cloud data pipelines; updating modeling principles and best practices; designing and architecting Snowflake solutions in Azure; guiding the team on configurations; ensuring data security and access controls; and acting as a data domain expert. The architect will be responsible for end-to-end data analytics design and architecture for Snowflake in Azure, including enterprise-wide RBAC, data modeling, DR solutions, performance optimization, security best practices, and private connectivity implementation.
Must have:
- Expertise in Azure and Snowflake integration
- Proficiency in SQL, Unix/Python scripting, performance tuning
- Deep understanding of relational and NoSQL data stores
- Implement Snowflake DWH solutions
- Develop ETL project requirements using Snowflake
- Improve cloud data pipelines
- Experience with data security and access controls in Snowflake
- Snowflake architecture expertise (RBAC, virtual warehouses, etc.)
- Experience with ADLS, ADF, Azure functions, App Service
Good to have:
- Snowflake certification
8 skills required
Job Details
Snowflake Data Architect
We are looking for a Snowflake Architect who will perform mission critical duties in our data engineering strategy, contributing to and leading the development of our Enterprise Data and Analytics Platforms. The Snowflake Architect will mainly be responsible for expanding, optimizing, and monitoring our expanding data pipelines through meticulous architecting, intelligent business logic, consistent data governance, testing and continuous delivery.
Responsibilities
1. Must have expertise in Azure and its integration with Snowflake to load/unload data.
2. Proficiency in complex SQL, Unix Shell/Python Scripting, performance tuning and database optimization techniques.
3. Deep understanding of relational as well as NoSQL data stores, methods and approaches (star and snowflake, dimensional modelling).
4. Implement Enterprise data warehouse solutions with Snowflake.
5. Develop project requirements for end-to-end ETL using Snowflake.
6. Improve existing data pipelines in cloud for data transformation and aggregation.
7. Make necessary on-going updates to modeling principles, processes, solutions, and best practices to ensure that the Snowflake is aligned with business needs of the environment.
8. Responsible for end-to-end data analytics design and architecture for Snowflake in Azure.
9. Guide the team to handle configurations for multiple departments/groups within single environment stack.
10. Experience with data security and data access controls and design in Snowflake.
11. Act as Data domain expert for Snowflake in a collaborative environment to provide demonstrated understanding of data management best practices and patterns.
12. Address technical inquiries concerning customization, integration, enterprise architecture and general feature / functionality of Snowflake.
Required Knowledge and Level of Experience
1. Certified Snowflake cloud data warehouse Architect (Desirable).
2. 8+ years of experience implementing data management solutions (Required).
3. Expertise in Snowflake concepts like setting up Resource monitors, RBAC controls, scalable virtual warehouse, SQL performance tuning, zero copy clone, time travel and automating them.
4. Must have worked on at least one enterprise-wide end to end implementation of snowflake including
a. Enterprise wide RBAC in snowflake
b. Data modelling for entire organizational data assets in snowflake
c. DR solution
d. Performance optimization
e. Best security practices in snowflake
f. Private connectivity implementation
5. Experience in Azure technologies such as ADLS, ADF, Azure functions, App Service etc.
6. SnowSQL Experience in developing stored Procedures writing Queries to analyze and transform data.
7. Design and Develop automated monitoring processes on Snowflake using combination of Python, PySpark, Bash with SnowSQL.
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