[Hiring] Snowflake Architect @Mpapan Neem Tree Private Limited

Role Description

We are seeking an experienced Snowflake Architect - Manager Level to lead the design, governance, and evolution of the enterprise data platform on Snowflake, while driving integration of AI/ML capabilities into the data ecosystem. This is a hands-on architecture role - the ideal candidate operates as a senior technical leader who sets standards, guides other engineers through influence and review (not formal management), and owns delivery of complex platform initiatives.

Qualifications

• 8+ years of experience in data engineering/architecture, including 4+ years hands-on with Snowflake in production environments
• Practical experience with Snowflake Cortex or equivalent LLM-in-warehouse capabilities
• Experience integrating AI/ML workflows (RAG, embeddings, vector search, model deployment) with cloud data platforms
• Proven ability to work independently and drive technical decisions with minimal oversight

Requirements

• Own end-to-end architecture of the Snowflake data platform: data modeling, ingestion, transformation, storage, and consumption layers.
• Architect solutions using Snowpark (Python/Java/Scala), Streams & Tasks, Dynamic Tables, Iceberg Tables, External Tables, and Data Sharing/Marketplace.
• Design integration patterns with cloud platforms (AWS/Azure/GCP), ETL/ELT tools (dbt, Fivetran, Matillion, Airflow), and BI tools (Tableau, Power BI, Looker).
• Define standards for performance optimization, warehouse sizing, and auto-suspend/scaling policies.
• Own cost optimization recommendations and monitor credit usage across the platform.
• Set data security standards - RBAC, masking, row-access policies, encryption - and monitor platform SLAs for availability, performance, and data freshness.
• Lead adoption of Snowflake Cortex (LLM functions, Cortex Analyst, Cortex Search) for natural-language analytics and AI-powered applications.
• Design and build Cortex Agents and Snowflake Intelligence agents to orchestrate multi-step reasoning across structured and unstructured data.
• Define and maintain Semantic Views to provide governed, business-friendly data models for natural-language querying and agentic consumption.
• Architect Snowpark ML pipelines for feature engineering, model training, and inference.
• Guide integration of external AI/LLM services (e.g., Anthropic, OpenAI, Azure OpenAI) via APIs, vector embeddings, and RAG patterns.
• Evaluate and implement vector/semantic search for unstructured data use cases.
• Partner with data science teams to operationalize ML models and ensure MLOps best practices within the Snowflake ecosystem.
• Act as the final technical authority on Snowflake-related design decisions; lead architecture review sessions.
• Provide technical guidance and code/design review to engineers working within the platform.
• Own project scoping, technical planning, and delivery of major architecture initiatives.
• Partner with product, analytics, security, and business stakeholders to translate requirements into scalable technical solutions.
• Produce architecture documentation, runbooks, and knowledge-transfer materials to ensure continuity of the platform.
• Collaborate with business and technology stakeholders to define data platform and AI roadmaps.
• Conduct demos, training sessions, and enablement workshops on Snowflake and AI/ML capabilities.
• Mentor junior engineers and support proposal/pre-sales activities where applicable.
• Manage project deliverables, risks, and client/stakeholder communications.

Benefits

• SnowPro Advanced Certification
• SnowPro Advanced: Data Engineer certification
• SnowPro Advanced: Data Scientist / Data Analyst Certification

Education

• Bachelor's Degree in Computer Science, Data Engineering, Information Systems, or related discipline.