Senior Data Engineer - Cloud Data Platform (Snowflake & dbt)

AssistRx transforms the patient journey through technology, helping patients access life-saving therapies faster and more efficiently. They are seeking a Senior Data Engineer to join their Cloud Data Platform team, focused on designing, building, and scaling their modern data platform using Snowflake and dbt.

Responsibilities:

• Design, build, and optimize Snowflake-centric data architectures to support enterprise analytics, reporting, and operational use cases
• Own dbt transformation layers, including model design, testing, documentation, and deployment best practices
• Implement scalable data modeling patterns (star schemas, data vault, dimensional models) aligned to business needs
• Develop and maintain reliable data pipelines integrating sources such as Salesforce, application databases, and external client data
• Ensure data quality through validation, testing, monitoring, and observability frameworks
• Optimize Snowflake performance and cost through query tuning, warehouse design, and efficient data modeling
• Partner closely with Analytics, BI, Product, and Engineering teams to deliver trusted, analytics-ready datasets
• Contribute to architectural standards, code reviews, and best practices across the CDP team
• Document data flows, models, and platform decisions to support long-term scalability and knowledge sharing
• Ensure data pipelines and models meet PHI / PII / HIPAA compliance requirements
• Support secure access patterns, role-based permissions, and data governance controls

Requirements:

• 6+ years of experience in data engineering, analytics engineering, or backend data development
• Advanced Snowflake expertise in a production environment (performance tuning, architecture, optimization)
• Strong dbt experience building and maintaining transformation layers at scale
• Expert-level SQL skills, including complex transformations and performance optimization
• Experience designing and supporting cloud-based data platforms (Snowflake preferred)
• Hands-on experience integrating data from SaaS platforms (e.g., Salesforce) and operational systems
• Familiarity with CI/CD concepts for analytics engineering (version control, deployments, testing)
• Strong understanding of data modeling best practices for analytics and reporting
• Experience in healthcare, life sciences, or regulated environments
• Python experience for data engineering or automation
• Familiarity with Azure-based data tooling (ADF, storage, compute)
• Exposure to BI tools such as Power BI, Tableau, or ThoughtSpot