Senior Data Engineer

Capital Rx is a full-service pharmacy benefit manager (PBM) and pharmacy benefit administrator (PBA) that is advancing the nation’s healthcare infrastructure. The Senior Data Engineer will build and maintain data models within Snowflake, ensuring data quality and collaborating with various teams to deliver reliable datasets.

Responsibilities:

• Build, test, and document Snowflake data models and business logic in dbt
• Apply and improve data quality, testing, observability, and lineage standards
• Collaborate with cross-functional partners to define data contracts and interfaces
• Contribute to Capital Rx’s modular data platform and client-specific data configurations
• Participate in design reviews; propose scalable, maintainable patterns
• Monitor pipeline health, troubleshoot incidents, and drive root-cause fixes
• Optimize cost and performance of jobs, storage, and queries with guidance
• Write clear documentation and support knowledge sharing
• Adhere to the Capital Rx Code of Conduct, including reporting of noncompliance

Requirements:

• Build, test, and document Snowflake data models and business logic in dbt
• Apply and improve data quality, testing, observability, and lineage standards
• Collaborate with cross-functional partners to define data contracts and interfaces
• Contribute to Capital Rx's modular data platform and client-specific data configurations
• Participate in design reviews; propose scalable, maintainable patterns
• Monitor pipeline health, troubleshoot incidents, and drive root-cause fixes
• Optimize cost and performance of jobs, storage, and queries with guidance
• Write clear documentation and support knowledge sharing
• Adhere to the Capital Rx Code of Conduct, including reporting of noncompliance
• 5+ years in data engineering, software engineering, or related field
• Strong SQL and Python; solid understanding of ETL/ELT and dimensional/data vault modeling
• Hands-on dbt experience (models, tests, documentation, deployments)
• Experience with orchestration (Dagster or Airflow) and scheduling best practices
• Familiarity with Spark/Databricks and cloud data warehouses (Snowflake preferred)
• CI/CD for data (Git-based workflows, environments), and basic IaC familiarity
• Data observability and testing (dbt tests, Great Expectations/Soda, lineage tools)
• Understanding of security, governance, and privacy for PII/PHI (HIPAA awareness)
• Effective communication and collaboration with technical and non-technical stakeholders
• Bonus if you have Exposure to healthcare data (claims, eligibility, provider directories)
• Performance tuning in Snowflake (warehouse sizing, clustering, caching)