What are the responsibilities and job description for the Snowflake Data Architect- Local to VA only position at Caliber Smart?
Role Name: Snowflake Data Architect
Location: Arlington, VA (Hybrid)
Duration :12 Months
F2F needed for Final round
Job Description
Key Responsibilities
Lead end-to-end data architecture and solution design for Snowflake-based data platforms, including logical/physical data models, ingestion patterns (batch, streaming, Snowpipe), storage layers (raw, curated, consumption/semantic), and consumption patterns for analytics, BI, and AI/ML.
Design and optimize scalable, high-performance data warehouses, data lakes, and lakehouse architectures on Snowflake, focusing on performance tuning, query optimization, cost management, workload/warehouse strategies, and auto-scaling.
Architect and implement AI-powered solutions using Snowflake Cortex, including Cortex LLM functions, Cortex Search for semantic/vector/RAG capabilities, Cortex Analyst for conversational analytics, Document AI, and integration with external LLMs (e.g., for fine-tuning, agents, and multimodal data processing).
Define and enforce data governance, security, and compliance frameworks (RBAC, row/column access policies, dynamic data masking, encryption, secure data sharing, and private listings).
Design data pipelines integrating with various sources (on-prem, cloud, SaaS) and orchestration tools; implement real-time capabilities using Streams, Tasks, and Snowpark (Python/Scala/Java).
Collaborate with data engineers, analysts, scientists, and business stakeholders to deliver governed, reusable data products that accelerate analytics and AI initiatives.
Provide technical leadership in migrations to Snowflake from legacy systems (e.g., on-prem warehouses, other clouds) and establish reference architectures, patterns, and standards.
Monitor platform health, optimize for cost/performance, and implement disaster recovery, replication, and high-availability strategies.
Mentor junior architects and engineers; conduct design reviews and promote best practices in data modeling (e.g., Data Vault, Kimball, or hybrid), semantic modeling, and AI-ready data foundations.
Required Qualifications
8 years of experience in data architecture, data engineering, or data platform roles, with at least 4 years specifically designing and optimizing solutions on Snowflake.
Deep expertise in Snowflake features: warehouses, resource monitors, zero-copy cloning, Time Travel, data sharing, Snowpark, Tasks/Streams, and security/governance controls.
Strong proficiency in SQL, data modeling (conceptual, logical, physical), ETL/ELT patterns, and cloud data platforms (AWS, Azure, or GCP).
Proven experience designing secure, scalable architectures for analytics, reporting, and machine learning workloads.
Solid understanding of data governance, quality, lineage, and compliance (e.g., GDPR, SOC2, HIPAA if applicable).
Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent experience).
Excellent communication, stakeholder management, and leadership skills.
Preferred Skills And Experience
Hands-on experience with Snowflake Cortex AI capabilities (Cortex Search, Cortex Analyst, LLM functions, vector embeddings, RAG patterns, and building AI agents or applications within Snowflake).
SnowPro Core, Advanced, or Architect certification(s).
Experience with modern data stack tools: dbt, Airflow, Kafka, Spark, Fivetran, Matillion, or similar.
Knowledge of AI/ML workflows, vector databases, semantic search, and integrating structured/unstructured data for generative AI.
Background in Data Vault 2.0, dimensional modeling, or domain-driven design.
Experience in regulated industries (finance, healthcare, pharma) or large-scale enterprise environments is a plus.
Best Regards,
Chetna
Chetna@smartcaliber.com
www.smartcaliber.com
Truth Lies in Heart
Location: Arlington, VA (Hybrid)
Duration :12 Months
F2F needed for Final round
Job Description
Key Responsibilities
Lead end-to-end data architecture and solution design for Snowflake-based data platforms, including logical/physical data models, ingestion patterns (batch, streaming, Snowpipe), storage layers (raw, curated, consumption/semantic), and consumption patterns for analytics, BI, and AI/ML.
Design and optimize scalable, high-performance data warehouses, data lakes, and lakehouse architectures on Snowflake, focusing on performance tuning, query optimization, cost management, workload/warehouse strategies, and auto-scaling.
Architect and implement AI-powered solutions using Snowflake Cortex, including Cortex LLM functions, Cortex Search for semantic/vector/RAG capabilities, Cortex Analyst for conversational analytics, Document AI, and integration with external LLMs (e.g., for fine-tuning, agents, and multimodal data processing).
Define and enforce data governance, security, and compliance frameworks (RBAC, row/column access policies, dynamic data masking, encryption, secure data sharing, and private listings).
Design data pipelines integrating with various sources (on-prem, cloud, SaaS) and orchestration tools; implement real-time capabilities using Streams, Tasks, and Snowpark (Python/Scala/Java).
Collaborate with data engineers, analysts, scientists, and business stakeholders to deliver governed, reusable data products that accelerate analytics and AI initiatives.
Provide technical leadership in migrations to Snowflake from legacy systems (e.g., on-prem warehouses, other clouds) and establish reference architectures, patterns, and standards.
Monitor platform health, optimize for cost/performance, and implement disaster recovery, replication, and high-availability strategies.
Mentor junior architects and engineers; conduct design reviews and promote best practices in data modeling (e.g., Data Vault, Kimball, or hybrid), semantic modeling, and AI-ready data foundations.
Required Qualifications
8 years of experience in data architecture, data engineering, or data platform roles, with at least 4 years specifically designing and optimizing solutions on Snowflake.
Deep expertise in Snowflake features: warehouses, resource monitors, zero-copy cloning, Time Travel, data sharing, Snowpark, Tasks/Streams, and security/governance controls.
Strong proficiency in SQL, data modeling (conceptual, logical, physical), ETL/ELT patterns, and cloud data platforms (AWS, Azure, or GCP).
Proven experience designing secure, scalable architectures for analytics, reporting, and machine learning workloads.
Solid understanding of data governance, quality, lineage, and compliance (e.g., GDPR, SOC2, HIPAA if applicable).
Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent experience).
Excellent communication, stakeholder management, and leadership skills.
Preferred Skills And Experience
Hands-on experience with Snowflake Cortex AI capabilities (Cortex Search, Cortex Analyst, LLM functions, vector embeddings, RAG patterns, and building AI agents or applications within Snowflake).
SnowPro Core, Advanced, or Architect certification(s).
Experience with modern data stack tools: dbt, Airflow, Kafka, Spark, Fivetran, Matillion, or similar.
Knowledge of AI/ML workflows, vector databases, semantic search, and integrating structured/unstructured data for generative AI.
Background in Data Vault 2.0, dimensional modeling, or domain-driven design.
Experience in regulated industries (finance, healthcare, pharma) or large-scale enterprise environments is a plus.
Best Regards,
Chetna
Chetna@smartcaliber.com
www.smartcaliber.com
Truth Lies in Heart