Snowflake Architect

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The Snowflake Architect will lead the design, development, and maintenance of advanced data infrastructure on the Snowflake platform. This role involves collaborating with cross-functional teams, providing technical leadership, and ensuring that the data architecture is scalable, secure, and aligned with business objectives. The ideal candidate will have extensive experience in data engineering, Snowflake optimization, and cloud-based data warehousing solutions.

• Architect & Design:
Lead the design and development of data architectures and scalable solutions on the Snowflake platform to support large-scale data analytics.

• Leadership & Mentorship:
Provide technical guidance and mentorship to junior data engineers, ensuring best practices are followed.

• ETL/ELT Strategy:
Develop and oversee the implementation of efficient ETL/ELT processes, using Snowflake's native features and third-party tools.

• Extensive Snowflake

Experience:

Deep expertise with Snowflake features, such as Snowpipe, Streams, Tasks, Materialized Views, Marketplace, and Data Sharing.

• APIs:
Strong expertise in extracting or ingesting data from APIs.

• Data Quality:
Knowledgeable with Data Quality concepts and best practices.

• Data Warehousing:
Strong experience in data modeling, data warehousing concepts (e.g., star/snowflake schemas), and big data technologies.

• SQL Mastery:
Advanced SQL proficiency with a focus on optimization, complex queries, and troubleshooting.

• Cloud Expertise:
Hands-on experience with cloud environments like AWS, GCP, or Azure, particularly in deploying and managing Snowflake clusters.

• ETL/ELT:
Proficiency with ETL/ELT tools such as Five Tran, Matillion, Talend, or Informatica, and hands-on experience with data integration processes.

• Performance Optimization:
Optimize Snowflake performance, including tuning of warehouses, queries, and data ingestion processes to ensure speed and efficiency.

• Data Governance:
Establish and enforce data governance, security, and compliance standards, ensuring the highest level of data integrity and privacy.

• Automation & Orchestration:
Implement automation and orchestration for data pipelines, leveraging Azure and Snowflake features.

•

Collaboration:

Work closely with data architects, data scientists, and business analysts to align data infrastructure with business needs and analytics requirements.

• Innovation & Best Practices:
Stay updated on the latest Snowflake features and best practices, and introduce new technologies or methodologies to improve the data infrastructure.

• Cloud Integration:
Lead cloud integration efforts, including deployment and maintenance of Snowflake on Azure.

• Documentation:
Create and maintain comprehensive technical documentation for data architecture, pipelines, and proces ses.

• Scripting & Automation:
Advanced scripting skills (e.g., Python, Bash) for automating data processes and integrating with CI/CD pipelines.

Machine Learning:

• • Strong experience creating and tuning machine learning models in Azure and Snowflake.

• Seniority level
  
  Mid-Senior level

• Employment type
  
  Full-time

• Job function
  
  Information Technology

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