Data Architect I_Snowflake Architect

Role Overview We seek an accomplished Snowflake Architect with deep expertise in Cortex AI/ML capabilities and dbt-based data transformation pipelines. This senior-level position requires 12+ years of experience designing and implementing enterprise-scale cloud data warehouse solutions. The successful candidate will architect advanced analytics platforms, mentor teams, and drive innovation in data intelligence. Key Responsibilities

• Design and architect enterprise-scale Snowflake Data Cloud solutions aligned with business, analytics, AI, and digital transformation objectives.
• Architect scalable data platforms leveraging Snowflake, Snowpark, dbt, Dynamic Tables, Streams & Tasks, and modern ELT best practices.
• Design cloud-native data architectures on AWS and Azure, integrating services such as S3, ADLS, Event Hubs, Kafka, IAM, Key Vault, and cloud-native security frameworks.
• Establish enterprise data governance, security, and compliance frameworks utilizing Snowflake Horizon Catalog, data lineage, masking policies, row- and column-level security, and secure data sharing.
• Lead the architecture and implementation of AI/GenAI solutions using Snowflake Cortex AI, including Cortex Agents, LLM-powered applications, semantic search, document intelligence, and RAG architectures.
• Define enterprise-wide dbt frameworks, data modeling standards, testing strategies, documentation practices, and CI/CD pipelines for scalable analytics delivery.
• Drive large-scale cloud modernization and migration initiatives from legacy data warehouses and on-premise platforms to Snowflake.
• Establish DataOps, CI/CD, Infrastructure as Code (Terraform), and automation standards to enable reliable and scalable platform operations.
• Optimize query performance, warehouse utilization, workload management, storage consumption, and platform costs through architecture best practices and FinOps principles.
• Evaluate and adopt emerging technologies such as Snowpark, Apache Iceberg, Openflow, Native Apps, Real-Time Data Processing, and Snowflake Marketplace capabilities.
• Conduct architecture reviews, define enterprise standards, assess technical risks, and ensure alignment with governance, security, and operational requirements.
• Provide technical leadership, stakeholder engagement, executive-level advisory, solution roadmap definition, and mentoring to engineering and architecture teams. Key Technologies
• Snowflake: Cortex AI, Cortex Agents, Snowpark, Horizon Catalog, Dynamic Tables, Streams & Tasks, Iceberg Tables, Openflow, Native Apps, Secure Data Sharing
• Data Engineering: dbt, ELT, Data Vault, Dimensional Modeling, DataOps, CI/CD
• Cloud: AWS (S3, IAM, Lambda, MSK, Glue), Azure (ADLS, Event Hubs, Data Factory, Key Vault, Azure DevOps)
• AI/GenAI: RAG, AI Agents, LLMs, Semantic Search, Vector Embeddings, Prompt Engineering
• Governance: Horizon Catalog, Data Lineage, Data Classification, RBAC, ABAC, Masking Policies