📋 Description

• Design scalable data models covering field, brand, patient, market access, and omnichannel
• Integrate and transform data from prescription and sales, claims, specialty pharmacy, patient hub
• Develop robust ETL/ELT pipelines and reusable, curated datasets for downstream analytics and
• Build analytical marts, semantic layers, and standardized KPI definitions to support consistent
• Design fact and dimension models, including star schemas and conformed dimensions, for large-scale
• Resolve and maintain accurate mappings across HCPs, HCOs, products, payers, geographies, and

🎯 Requirements

• 5-8+ years of experience in analytics, data engineering, or a closely related field.
• 3+ years of experience working with commercial pharmaceutical or biotechnology data (preferred).
• Strong understanding of commercial pharma including sales and field effectiveness, patient
• Advanced SQL skills with experience working with large and complex commercial datasets.
• Strong Python skills for data processing, validation, automation, and workflow development.
• Proven experience developing ETL/ELT pipelines using dbt or similar data transformation

🎁 Benefits

• Full-time opportunity within a technology-focused environment.
• Opportunity to work on complex commercial pharmaceutical data and analytics initiatives.
• Exposure to diverse healthcare data sources including sales, prescriptions, claims, specialty
• Opportunity to work with modern data platforms such as Snowflake and Databricks.
• Hands-on experience with advanced engineering, modeling, ETL/ELT, and analytics technologies.
• Opportunity to contribute to data products that support commercial decision-making and field