Snowflake Data Architect

As a Snowflake Lead with experience, and additional expertise in ETL tools and DBT, youwill be entrusted with a pivotal role in designing, implementing, and managing Snowflake solutions to driveefficient data management and analytics. Your leadership will be instrumental in guiding the teamtodeliver high-quality, scalable, and optimized data solutions. Additionally, your proficiency in ETL andDBTwill enhance the organization's data processing capabilities Roles & Responsibilities 1. Perform analysis on existing Data Storage system and development of Data Solutions inSnowflake 2. Design the data warehouse and provide guidance to the team in implementation using Snowflake SnowSQL 3. Define and communicate best practices, coding standards, and architectural guidelines for Snowflake development. 4. Collaborate with stakeholders to understand business requirements and translate themintoeffective Snowflake data solutions. 5. Architect Snowflake data models, schemas, and pipelines aligned with the organization's datastrategy and industry best practices. 6. Lead the design and development of complex ETL processes and data transformations usingSnowflake, as well as additional ETL tools like [list specific tools]. 7. Ensure seamless data integration from various sources into Snowflake while maintaining dataquality and integrity. 8. Leverage your experience with DBT (Data Build Tool) to transform raw data into well-structured, business-ready data models. 9. Design and manage DBT workflows, ensuring consistent and reliable data transformations. 10. Identify and address performance bottlenecks in Snowflake queries, data loading, and transformations. 11. Implement optimization techniques such as caching, indexing, and partitioning to enhancequery performance. 12. Leverage your expertise in ETL tools to streamline data movement, transformation, and loadingprocesses beyond Snowflake. 13. Evaluate, select, and integrate ETL tools that complement the Snowflake ecosystemandenhance overall data processing efficiency. 14. Work closely with cross-functional teams including data scientists, analysts, and business stakeholdersto understand their data requirements and deliver optimalsolutions. 15. Facilitate communication between technical and non-technical teams to ensure successful project outcomes. 16. Hands-on experience in Python 17. Good hands-on experience in converting Source Independent Load, Post Load Process, StoredProcedure, SQL to Snowflake 18. Experience in working on migrating data from on-premises databases and files to Snowflake19. Strong understanding of ELT / ETL and integration concepts and design best practices. Classification : Internal 20. Experience in performance tuning of the snow pipelines and should be able to trouble shoot theissue quickly. 21. Experience in Snowsql, Snowpipe, and Snowpark. OtherQualifications 1. Experience in data engineering, data warehousing, and analytics. 2. Strong hands-on experience with Snowflake, including architecture design, ETL development, and performance optimization. 3. Proficiency in ETL tools such as [list specific tools] and experience with DBT. 4. Familiarity with cloud platforms (e.G., AWS, Azure, GCP) and their data services. 5. Proven leadership experience, including managing technical teams and projects. 6. Excellent problem-solving skills and ability to analyze complex technical challenges. 7. Effective communication skills and a collaborative approach to working with diverse teams

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