Overview
Skills
Job Details
Job Summary:
We are seeking a skilled and experienced Snowflake Architect to design, implement, and optimize cloud data warehouse solutions using Snowflake. The ideal candidate will have deep expertise in data architecture, cloud platforms, and best practices for designing scalable, secure, and efficient data solutions.
Key Responsibilities:
Lead the design and implementation of Snowflake-based data warehouse and analytics solutions.
Define data architecture, integration patterns, and governance processes for enterprise-scale Snowflake environments.
Collaborate with business stakeholders, data engineers, and analysts to understand requirements and deliver robust data models.
Optimize Snowflake performance, including query optimization, resource management, and cost control.
Establish best practices for data loading, transformation (ETL/ELT), security, and data lifecycle management.
Integrate Snowflake with other cloud services (e.g., AWS, Azure, Google Cloud Platform), BI tools, and downstream systems.
Provide guidance and mentorship to development teams on Snowflake development and cloud data engineering principles.
Stay up to date with Snowflake features, industry trends, and emerging technologies to drive continuous improvement.
Required Qualifications:
Bachelor s or Master s degree in Computer Science, Information Systems, or related field.
7+ years of experience in data warehousing and data architecture.
3+ years of hands-on experience with Snowflake design, development, and administration.
Strong understanding of cloud platforms (AWS, Azure, or Google Cloud Platform) and their data services.
Expertise in SQL, data modeling (dimensional & normalized), and ELT/ETL processes.
Experience with data integration tools (e.g., Informatica, Talend, Matillion, Fivetran) and orchestration tools (e.g., Airflow).
Solid knowledge of data security, privacy, and governance standards.
Preferred Qualifications:
Snowflake certification (e.g., SnowPro Advanced: Architect).
Experience with CI/CD pipelines and DevOps practices in data projects.
Knowledge of Python, Scala, or other scripting languages for data processing.
Soft Skills:
Excellent communication and interpersonal skills.
Strong problem-solving abilities and attention to detail.
Ability to work independently as well as part of a collaborative team.