Data & Analytics Engineer – Commercial Pharma
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Summary
Data & Analytics Engineer building commercial analytics for a pharma organization: designing data models, integrating Rx/sales, claims, specialty pharmacy and CRM data, and developing ETL/ELT pipelines and curated datasets. Core stack includes SQL, Python, dbt, and Snowflake or Databricks.
QUALIFICATIONS & TECHNICAL EXPERTISE
- Design data models across field, brand, patient, access and omnichannel
- Integrate Rx/sales, claims, specialty pharmacy, hub, CRM and digital data
- Develop ETL/ELT pipelines and reusable curated datasets.
- Resolve HCP, product, payer, geography and territory mapping
- Implement data quality and source-to-target validation checks
- Create marts, semantic layers and standardized KPI logic.
Commercial Pharma Experience
- 5 to 8+ years in analytics or data engineering
- 3+ years with pharma or biotech commercial data preferred
- Sales and field effectiveness
- Patient and market access analytics
Data Modeling Expertise
- Fact and dimension design
- Star and conformed dimensions
- Analytical marts and semantic layers
- HCP/HCO affiliation and NPI matching
Engineering & Platforms
- Advanced SQL on large commercial datasets
- Python for processing, validation and automation
- Strong ETL/ELT development; dbt or similar
- Snowflake, Databricks or comparable platforms
Commercial Data Expertise
- IQVIA Xponent and PlanTrak Rx
- Specialty pharmacy and patient hub feeds
- CRM (Veeva/Salesforce) activity