Data Architect

About the Role We're looking for a hands-on Data Architect who combines deep architectural thinking with real, hands-on engineering ability. This is not a "design-only" architect role—you'll be expected to code, build, and guide pipelines yourself while also owning the bigger picture: architecture, standards, stakeholder alignment, and end-to-end delivery. You'll bridge business needs with scalable, production-grade data platforms across Snowflake , Data Engineering, Data Quality, AI/ML enablement, Agentic AI solutions, and downstream analytics consumption. Key Responsibilities Architecture & Design Design and own end-to-end enterprise data architecture with Snowflake as the core data platform, leveraging Medallion (Bronze/Silver/Gold) architecture, Lakehouse patterns, and modern cloud data architectures. Define data modelling standards, ingestion strategies, governance, and storage/compute optimization across Snowflake, Databricks, Microsoft Fabric, and Azure. Architect scalable, secure, and high-performance solutions for BI, Analytics, AI/ML, Agentic AI, APIs, and enterprise applications. Establish enterprise standards for scalability, security, metadata management, lineage, observability, cost optimization, and governance. Hands-On Engineering Personally build and develop production-grade data pipelines using SQL, Python, Snowpark, and PySpark. Design, develop, and optimize Snowflake-native ELT pipelines using Snowpipe, Dynamic Tables, Streams & Tasks, and Snowpark. Modernize legacy ETL pipelines into scalable cloud-native architectures following industry best practices. Build reusable APIs and data services for enterprise applications and downstream systems. Implement enterprise Data Quality frameworks with validation, reconciliation, anomaly detection, monitoring, and alerting. Optimize Snowflake warehouses, Spark jobs, Delta tables, and end-to-end pipeline performance. Agentic AI & AI Enablement Design enterprise data architectures that enable AI Agents, Copilots, Retrieval-Augmented Generation (RAG), and LLM-powered applications. Build pipelines supporting vector search, embeddings, semantic search, and enterprise knowledge repositories. Integrate Snowflake Cortex AI, Cortex Search, Cortex Analyst, Azure AI Foundry, Microsoft AI Foundry, LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, or similar AI orchestration frameworks. Design secure AI-ready data platforms with governance, lineage, RBAC, and metadata management. Develop ML-ready datasets and feature engineering pipelines supporting Machine Learning and Generative AI workloads. Team Leadership & Stakeholder Management Mentor engineering teams on architecture, coding standards, performance optimization, and engineering best practices. Partner with business and product stakeholders to translate business requirements into scalable technical solutions. Own the complete Software Development Life Cycle (SDLC), including architecture, development, testing, deployment, monitoring, and production support. Drive architecture reviews, technical governance, and engineering excellence across the organization. Platform & Ecosystem Work extensively across Snowflake, Microsoft Azure, Microsoft Fabric, Databricks, and modern cloud-native ecosystems. Build secure, governed, scalable, and AI-ready enterprise data platforms. Implement CI/CD, Infrastructure as Code (IaC), monitoring, logging, and observability across data platforms. Required Skills & Experience Proven experience in Data Engineering and Data Architecture with strong hands-on development expertise. Expert-level SQL, Python, Snowpark, PySpark, and Apache Spark. Strong expertise in Snowflake , including Snowsight, Snowpark, Cortex AI, Cortex Search, Cortex Analyst, Snowpipe, Dynamic Tables, Streams & Tasks, CLI, Horizon Catalog, Tags, Data Sharing, and Performance Optimization. Strong expertise in Databricks , including Delta Lake, Unity Catalog, Delta Live Tables (DLT), Spark Optimization, Workflows, and MLflow. Strong understanding of Microsoft Fabric and Azure Data Platform. Deep expertise in Medallion Architecture, Lakehouse Architecture, Data Mesh, Data Vault, and modern ELT/ETL frameworks. Experience designing enterprise Data Quality frameworks using Great Expectations, Soda, Deequ, or custom frameworks. Experience developing REST APIs and enterprise data service layers. Strong understanding of AI/ML lifecycle, Feature Engineering, MLOps, LLM integration, and Agentic AI architectures. Experience implementing enterprise governance, metadata management, data lineage, RBAC, masking policies, and security frameworks. Experience with Git, Azure DevOps, GitHub Actions, CI/CD, automated testing, and release management. Excellent stakeholder communication, solution architecture, and technical leadership skills. Technology Stack Cloud & Data Platforms Snowflake (Snowpark, Cortex AI, Cortex Search, Cortex Analyst, Snowsight, Snowpipe, Dynamic Tables, Streams & Tasks, Horizon Catalog, Native Apps, Data Sharing) BigQuery Microsoft Azure Microsoft Fabric Databricks Azure Data Lake Storage Gen2 (ADLS Gen2) Azure Synapse Analytics Data Engineering & Processing SQL Python Snowpark PySpark Apache Spark Delta Lake Delta Live Tables (DLT) Azure Data Factory (ADF) Microsoft Fabric Data Factory Apache Airflow Data Architecture & Modeling Medallion Architecture (Bronze/Silver/Gold) Lakehouse Architecture Data Mesh Data Vault Star Schema Dimensional Modeling Data Quality & Governance Snowflake Governance (Tags, Masking Policies, Row Access Policies, Horizon Catalog) Great Expectations Soda Unity Catalog Microsoft Purview Data Lineage Metadata Management Agentic AI & AI/ML Snowflake Cortex AI Cortex Search Cortex Analyst Azure AI Foundry Microsoft AI Foundry Azure OpenAI OpenAI APIs LangChain LangGraph Semantic Kernel CrewAI AutoGen Model Context Protocol (MCP) Retrieval-Augmented Generation (RAG) Vector Databases (Azure AI Search, Pinecone, Weaviate, Milvus, ChromaDB) MLflow APIs & Integration REST APIs FastAPI GraphQL Azure Functions Event Grid Azure Service Bus DevOps & CI/CD Git GitHub GitHub Actions Azure DevOps Terraform Docker Kubernetes BI & Analytics Power BI Tableau Microsoft Fabric Real-Time Intelligence Semantic Models DAX Nice to Have SnowPro Core and SnowPro Advanced Certifications Databricks Certified Data Engineer Professional Microsoft Fabric Analytics Engineer (DP-600) Azure Data Engineer Associate (DP-203) Azure AI Engineer Associate (AI-102) Experience with Kafka, Azure Event Hubs, Apache Flink, or Spark Structured Streaming. Experience designing and implementing enterprise AI Agents, Multi-Agent Systems, MCP Servers, RAG applications, and Knowledge Graphs. Experience with Vector Databases such as Azure AI Search, Pinecone, Weaviate, Milvus, or ChromaDB. Experience working with enterprise data governance, FinOps, and cloud cost optimization across Snowflake and Azure.