Data Architect

Data Architect

Pay Range: $55hr - $60hr

Requirement/Must Have:

• 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.

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.

Nice to Have:

• 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.