Data Modeler Pharma Domain (Databricks)

Job Title : Data Modeler Pharma Domain (Databricks)

Location : Indianapolis, IN 46225 (Onsite)

About the Role:

We are seeking an experienced Data Modeler with expertise in data modeling and Databricks to join our team in the pharmaceutical domain. The ideal candidate will be responsible for designing, developing, and maintaining logical and physical data models that align with business objectives. This role requires a strong understanding of pharma data, regulatory requirements, and industry best practices for handling sensitive and complex datasets.

Key Responsibilities:

• Design, develop, and maintain conceptual, logical, and physical data models to support pharma business processes and analytics.
• Collaborate with stakeholders, business analysts, and data engineers to gather requirements and translate them into scalable data models.
• Work on Databricks Lakehouse environment to enable advanced analytics, machine learning, and reporting.
• Ensure data governance, integrity, and compliance with pharma regulatory standards (GxP, HIPAA, FDA 21 CFR Part 11, etc.).
• Optimize and maintain data models to support large-scale pharma datasets including clinical trials, R&D, commercial, and manufacturing data.
• Collaborate with data engineers to design and implement ETL/ELT pipelines within Databricks.
• Document metadata, data dictionaries, and maintain a repository of reusable modeling artifacts.
• Ensure data quality, security, and privacy controls are integrated into data models.

Required Skills & Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, or related field.
• Proven experience as a Data Modeler (5+ years preferred).
• Strong hands-on expertise in conceptual, logical, and physical data modeling using tools like Erwin, PowerDesigner, or similar.
• Proficiency with Databricks, PySpark, SQL, and data lakehouse architectures.
• Solid understanding of data warehousing, ETL/ELT, and data integration patterns.
• Experience working with pharma datasets (clinical, R&D, regulatory, manufacturing, or commercial data).
• Familiarity with data governance and compliance frameworks within the pharmaceutical industry.
• Strong collaboration, documentation, and communication skills.

Preferred Qualifications:

• Experience with cloud platforms (Azure, AWS, or Google Cloud Platform) and their data services.
• Exposure to data mesh, MDM (Master Data Management), and ontology frameworks in pharma.
• Knowledge of machine learning pipelines in Databricks.
• Understanding of real-world evidence (RWE), clinical trial management systems (CTMS), or pharmacovigilance data.