Architect and implement scalable data warehouse solutions using Snowflake
Design end-to-end data architectures including ingestion, transformation, storage, and consumption layers
Develop and optimize data models (dimensional and normalized) to support analytics and reporting use cases
Lead integration of multiple data sources including commercial, clinical, and third-party vendor data
Define and implement ETL/ELT pipelines using modern tooling (e.g., DBT, Azure Data Factory, Databricks)
Establish data governance, security, and data quality frameworks aligned with regulatory requirements
Optimize Snowflake performance, cost management, and workload scaling strategies
Collaborate with stakeholders to define data strategy, architecture roadmaps, and platform evolution
Support downstream analytics, BI (e.g., Power BI), and data science initiatives
Provide technical leadership and mentorship to data engineering teams

10+ years of experience in data architecture, data warehousing, or data engineering
Experience in life sciences, biotech, or healthcare data (commercial, clinical, RWD, etc.)
3+ years of hands-on experience with Snowflake in a solution architecture role
Strong expertise in SQL and data modeling (dimensional modeling, data vault, etc.)
Experience designing and implementing cloud-based data platforms (Azure preferred, AWS acceptable)
Hands-on experience with modern data stack tools (DBT, Databricks, MuleSoft, etc.)
Experience integrating complex datasets (e.g., transactional, third-party, semi-structured data)
Strong understanding of data governance, data quality, and security best practices
Excellent communication skills with ability to interface between business and technical teams.

Snowflake Solution Architect

Key skills