Snowflake Architect

Promaynov Advisory Services Pvt. Ltd; Bengaluru; On-site; INR 4,000,000 - 6,500,000; Full time

Job summary

Promaynov Advisory Services Pvt. Ltd. seeks a Snowflake Architect – Manager level to lead enterprise data platform design and governance on Snowflake, driving AI/ML integration within the data ecosystem.

This is a hands-on architecture role with influence over engineering and delivery of complex platform initiatives. The candidate will own end‑to‑end data platform architecture, guide cortex adoption, and collaborate with security, product, and analytics stakeholders to ensure scalable, governed

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.

Responsibilities

• 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 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.

Skills

Snowflake Architecture

Snowpark

AI/ML integration

Data governance

Cloud platforms (AWS/Azure/GCP)

Leadership influence

Education

Bachelor's Degree in Computer Science or related

Tools

dbt

Fivetran

Matillion

Airflow

Tableau

Power BI

Job description

Role Level: Manager (M) Practice: AI & Data Focus Areas: Snowflake Architecture, Snowpark, Snowflake Cortex & AI/ML Integration, Data Governance, Cloud Data Platforms, RAG & Vector Search. Location: Bangalore/Kolkata/Hyderabad

Role Summary

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.

Experience

• 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

Key Responsibilities

Platform Architecture

• 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).

Performance, Cost & Security

• 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.

AI/ML Integration

• 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.

Technical Leadership & Delivery

• 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.

Stakeholder Management

• 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.

Preferred Certifications

• 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.