About the role
Role Overview : Job Description: Data Architect: Snowflake Position Location: Markham, ON, CA Position: Fulltime Mode: Hybrid (Mandatorily need to visit office 3 days (Monday/ Tuesday/ Wednesday))
Job Description:
Role Purpose: The purpose of the Data Architect: Snowflake role is to: • Architect and implement advanced data solutions using Snowflake on AWS, ensuring scalable, secure, and high-performance data environments. • Migration of the existing Datawarehouse solution to Snowflake • Technology platform evaluations in the data and analytics space • Collaborate with cross-functional teams (data engineers, AI engineers, business, solution architects) to translate business requirements into technical solutions aligned with data strategy. • Ensure data governance, security, and compliance within the Snowflake ecosystem, adhering to regulatory and organizational standards. Experience and Capabilities • Extensive experience (8+ years) in data architecture and engineering, with a proven track record in large-scale data transformation programs, ideally in insurance or financial services. • Proven experience in architecting and implementing advanced data solutions using Snowflake on AWS, • Expertise in design and orchestrating data acquisition pipelines using AWS Glue for ETL/ELT, Snowflake OpenFlow and Apache Airflow for workflow automation, enabling seamless ingestion of different data from diverse sources. • Proven experience in DBT to manage and automate complex data transformations within Snowflake, ensuring modular, testable, and version-controlled transformation logic. • Experience in implementing the lake house solution, Medallion architecture for financial or insurance carriers • Experience in optimizing and tune Snowflake environments for performance, cost, and scalability, including query optimization and resource management, • Experience in architecting/lead migration of workloads from Cloudera to Snowflake • Design Streamlit apps and define new capabilities and data products leveraging snowflake ML and LLOPS capabilities. • Experience in evaluating the data technology platform including data governance suites, data security products • Exposure to enterprise Datawarehouse solution like Cloudera, AWS Redshift and informatica tool sets- IDMC, powercenter, BDM • Develop robust data models and data pipelines to support data transformation, integrating multiple data sources and ensuring data quality and integrity. • Document architecture, data flows, and transformation logic to ensure transparency, maintainability, and knowledge sharing across teams. • Strong knowledge of data lifecycle mgmt., data retention, data modelling and working knowledge of cloud computing, and modern development practices. • Experience with data governance, metadata management, and data quality frameworks (e.g., Collibra, Informatica). • Experience in converting policy/data conversion from legacy to modern platform • Deep expertise in Snowflake (Snowpro advanced certification preferred), with hands-on experience delivering Snowflake as an enterprise capability. • Hands-on experience with AWS Glue for ETL/ELT, Apache Airflow for orchestration, and dbt for transformation (preferably deployed on AWS ECS). • Proficiency in SQL, data modeling, ETL/ELT processes, and scripting languages (Python/Java). • Familiarity with data mesh principles, data product delivery, and modern data warehousing paradigms.
Similar Jobs
About the role
Role Overview : Job Description: Data Architect: Snowflake Position Location: Markham, ON, CA Position: Fulltime Mode: Hybrid (Mandatorily need to visit office 3 days (Monday/ Tuesday/ Wednesday))
Job Description:
Role Purpose: The purpose of the Data Architect: Snowflake role is to: • Architect and implement advanced data solutions using Snowflake on AWS, ensuring scalable, secure, and high-performance data environments. • Migration of the existing Datawarehouse solution to Snowflake • Technology platform evaluations in the data and analytics space • Collaborate with cross-functional teams (data engineers, AI engineers, business, solution architects) to translate business requirements into technical solutions aligned with data strategy. • Ensure data governance, security, and compliance within the Snowflake ecosystem, adhering to regulatory and organizational standards. Experience and Capabilities • Extensive experience (8+ years) in data architecture and engineering, with a proven track record in large-scale data transformation programs, ideally in insurance or financial services. • Proven experience in architecting and implementing advanced data solutions using Snowflake on AWS, • Expertise in design and orchestrating data acquisition pipelines using AWS Glue for ETL/ELT, Snowflake OpenFlow and Apache Airflow for workflow automation, enabling seamless ingestion of different data from diverse sources. • Proven experience in DBT to manage and automate complex data transformations within Snowflake, ensuring modular, testable, and version-controlled transformation logic. • Experience in implementing the lake house solution, Medallion architecture for financial or insurance carriers • Experience in optimizing and tune Snowflake environments for performance, cost, and scalability, including query optimization and resource management, • Experience in architecting/lead migration of workloads from Cloudera to Snowflake • Design Streamlit apps and define new capabilities and data products leveraging snowflake ML and LLOPS capabilities. • Experience in evaluating the data technology platform including data governance suites, data security products • Exposure to enterprise Datawarehouse solution like Cloudera, AWS Redshift and informatica tool sets- IDMC, powercenter, BDM • Develop robust data models and data pipelines to support data transformation, integrating multiple data sources and ensuring data quality and integrity. • Document architecture, data flows, and transformation logic to ensure transparency, maintainability, and knowledge sharing across teams. • Strong knowledge of data lifecycle mgmt., data retention, data modelling and working knowledge of cloud computing, and modern development practices. • Experience with data governance, metadata management, and data quality frameworks (e.g., Collibra, Informatica). • Experience in converting policy/data conversion from legacy to modern platform • Deep expertise in Snowflake (Snowpro advanced certification preferred), with hands-on experience delivering Snowflake as an enterprise capability. • Hands-on experience with AWS Glue for ETL/ELT, Apache Airflow for orchestration, and dbt for transformation (preferably deployed on AWS ECS). • Proficiency in SQL, data modeling, ETL/ELT processes, and scripting languages (Python/Java). • Familiarity with data mesh principles, data product delivery, and modern data warehousing paradigms.