What are the responsibilities and job description for the Snowflake Architect with AWS position at Compunnel Inc.?
Job Summary We are seeking an experienced Snowflake Architect with strong expertise in data architecture, Snowflake administration, Data Vault, ODS modeling, and dimensional data modeling. This role will be responsible for designing scalable enterprise data platforms, establishing architecture and governance standards, optimizing Snowflake environments, and managing end-to-end data lifecycle requirements across ODS, standardized, data warehouse, and data mart layers. Key Responsibilities Define and lead enterprise data architecture strategies across ODS, standardized, data warehouse, and data mart layers. Design end-to-end data pipelines to establish a unified and governed data ecosystem within Snowflake. Establish standards for data ingestion, transformation, storage, and consumption across data architecture layers. Drive data modeling best practices, schema evolution, and data integration strategies. Ensure adherence to data quality, lineage, governance, and security frameworks. Architect and manage Snowflake environments across development, QA, and production with strong governance controls. Implement RBAC, security policies, and access control mechanisms within Snowflake environments. Optimize Snowflake performance, cost, scalability, and workload management. Lead Snowflake administration activities including monitoring, tuning, and capacity planning. Design and implement Data Vault models and ODS layers to support scalable ingestion and auditability. Build dimensional models including fact and dimension structures using Star and Snowflake schemas for business consumption. Define data structures across standardized and curated layers for analytics and reporting. Design and optimize ETL/ELT pipelines using SQL, Snowpark, Python, and cloud-native technologies. Leverage Snowflake capabilities including bulk loading, event-driven task graphs, directory tables, streams, Snowpark, and Python procedures and scripting. Design and support AWS-based data integration and processing solutions using services such as Amazon S3, AWS Lambda, AWS Step Functions, and AWS CodeBuild. Collaborate with business, data, and engineering teams to translate requirements into scalable data architecture solutions. Support integration with analytics, reporting, and downstream enterprise systems. Establish and maintain data architecture standards, governance practices, and security controls. Contribute to data modernization initiatives and evaluate emerging Snowflake and cloud technologies. Required Qualifications Strong experience in enterprise data architecture and the Snowflake ecosystem. Expertise in Snowflake administration, RBAC, security, performance tuning, and workload optimization. Deep knowledge of Data Vault and dimensional data modeling. Strong understanding of Enterprise Data Warehouse architecture, including ODS, standardized, data warehouse, and data mart layers. Strong expertise in SQL, data pipelines, and data optimization. Strong hands-on experience with Snowflake Core capabilities, including bulk loading, tasks, task graphs, directory tables, streams, Snowpark, and Python procedures or scripting. Strong experience with AWS cloud architecture and data services. Experience with AWS S3, notifications, Lambda, Step Functions, and CodeBuild. Strong experience with SparkSQL. Experience designing and optimizing ETL/ELT pipelines and data integration frameworks. Experience with data governance, data quality, lineage, security, and access control. Experience with Snowflake environment administration across development, QA, and production. Strong analytical, troubleshooting, architecture, and problem-solving skills. Preferred Qualifications Experience with Talend ETL and Talend Studio. Experience with Terraform and Infrastructure as Code. Experience with Snowpark and dbt. Experience integrating machine learning and AI capabilities with data platforms. Experience with MLOps practices and technologies. Exposure to large-scale data modernization programs. Experience with Qlik and enterprise analytics platforms. Experience supporting data architecture initiatives within insurance or financial services environments. Education: Bachelors Degree