Data Architect I

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