Data Integration Architect

As a Data Integration Architect, your role involves the development and optimization of data solutions using Snowflake and DBT. You will be responsible for ensuring efficient data integration, transformation, and real-time analytics. Collaboration with cross-functional teams to translate business requirements into technical solutions, maintaining data integrity and compliance, and driving innovation in data engineering practices are key aspects of your responsibilities. Key Responsibilities: - Design, build, and maintain robust Snowflake architectures and data pipelines using DBT for efficient data integration and transformation. - Assess legacy data warehouses and identify areas for performance improvement. - Optimize the performance of Snowflake databases and DBT models to ensure high efficiency and scalability of data solutions. - Ensure data integrity, quality, and compliance with data governance and security policies. - Work closely with analysts and business stakeholders to understand requirements and deliver effective data solutions. - Develop scalable DBT solutions capable of handling increasing data volumes and complexity. - Diagnose and resolve issues related to Snowflake infrastructure and data pipelines. - Optimize Snowflake performance, including query tuning. - Collaborate with stakeholders to gather requirements and design scalable solutions. Qualifications Required: - Deep understanding of Snowflake architecture and performance optimization. - Expertise in SQL and data modeling (both relational and dimensional). - Design and manage efficient ETL DBT models for data transformation. - Prior experience in data warehouse migrations (Good to have). - Basic knowledge of integrating machine learning models and AI algorithms with data pipelines (Good to have). - Experience with DevOps practices and continuous integration/continuous deployment (CI/CD) pipelines (Good to have). - Understanding of compliance standards such as GDPR, HIPAA, etc (Good to have). - Minimum of 8+ years of experience in data engineering, with a focus on Snowflake and DBT. - Proven track record of designing and implementing data solutions in complex environments. - Relevant certifications in Snowflake and other cloud technologies are highly desirable. - Bachelors or Masters degree in Computer Science, Information Technology, Data Science, or a related field.,