Position: Cloud Architect - Snowflake
Location: Pune/Nagpur
Type of Employment: Full-time
Purpose of the Position:
The Snowflake Architect will be responsible for leading the design, implementation, and optimization of enterprise-scale data solutions on Snowflake. This role is responsible for building a scalable, secure, and high-performance data architecture that aligns with organizational data and analytics objectives.
The architect will collaborate closely with business stakeholders, analytics teams, and engineering functions to enable high-quality, trusted data for reporting, advanced analytics, and AI-driven use cases. Additionally, the role will drive best practices in data modelling, performance tuning, cost optimization, and data governance, while providing architectural guidance and ensuring adherence to enterprise standards.
Key Result Areas (KRAs):
Data Architecture Design
- Design and evolve scalable, secure, and high-performance data architectures on Snowflake aligned with enterprise data strategy and business objectives.
- Establish best practices for data modelling (dimensional, data vault, etc.), ingestion frameworks, and storage optimization.
Data Quality & Governance
- Define and enforce data quality frameworks, governance policies, and standards across data platforms.
- Ensure data integrity, consistency, and compliance through robust validation, lineage, and monitoring mechanisms.
- Implement security best practices including RBAC, data masking, encryption, and row-level access controls aligned with regulatory standards (GDPR, HIPAA, SOC2).
Performance & Cost Optimization
- Drive performance tuning of Snowflake workloads including query optimization, warehouse sizing, clustering, and caching strategies.
- Optimize ETL/ELT pipelines for efficiency, scalability, and cost management.
- Establish proactive monitoring and continuous improvement mechanisms for platform performance.
AI/ML & Advanced Analytics Enablement
- Leverage Snowflake Cortex capabilities to enable AI-driven use cases within the data ecosystem.
- Design and implement Conversational BI solutions (e.g., Cortex Analyst) to enable natural language access to structured data.
- Build and operationalize Retrieval-Augmented Generation (RAG) pipelines to securely integrate enterprise data with LLMs.
- Ensure AI solutions are governed, explainable, and aligned with enterprise data security principles.
Collaboration & Technical Leadership
- Partner with cross-functional stakeholders including data engineering, analytics, and business teams to translate requirements into scalable solutions.
- Provide architectural guidance, conduct design reviews, and mentor engineering teams on best practices.
Innovation & Continuous Improvement
- Stay current with emerging trends in cloud data platforms, AI/ML, and Snowflake advancements.
- Identify and implement innovative approaches to improve data processing, analytics capabilities, and time-to-insight.
- Drive adoption of modern data practices including automation, data observability, and AI-enabled analytics.
