Sr Data Modeler

Overview

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care.

What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you.

Cover My Meds  Technology is seeking a Senior Data Modeler to join our Data Engineering team. Our group is a highly technical mix of engineers, analysts, and architects focused on building high-quality, scalable, and repeatable data solutions. We partner with business units across the company to deliver trusted data that powers both day-to-day healthcare operations and advanced analytics—ultimately helping more people get the medicines they need to live healthier lives.

The Sr. Data Modeler will design, develop, and maintain data models that support transactional systems (FHIR/canonical models, operational data stores, interoperability) and analytical environments (data warehouses, data marts, BI dashboards, and advanced analytics platforms). You'll ensure data is structured efficiently to enable real-time operational workflows as well as large-scale analytical insights.

* Our preferred candidate will reside in the Columbus, OH area; however, we will consider a highly qualified candidate who resides in our other hub cities of Atlanta GA or Irving TX, or a fully remote candidate.

* At this time, we are not able to offer sponsorship for employment visas. This includes individuals currently on F-1 OPT, STEM OPT, or any other visa status that would require future sponsorship. Candidates must be authorized to work in the United States on a permanent basis without the need for current or future sponsorship.

• Design and implement conceptual, logical, and physical data models for both transactional healthcare applications and analytical/reporting use cases.
• Develop and maintain FHIR-aligned and canonical data models to support interoperability, patient/provider/drug mastering, and integration with FHIR servers.
• Design and optimize analytical models (dimensional, wide-table, Data Vault) that power dashboards, self-service analytics, and AI/ML workloads.
• Partner with product engineering, DBAs, data engineers, and business analysts to translate business requirements into scalable data architecture.
• Support ETL/ELT and real-time data pipelines to ensure efficient integration, transformation, and availability across operational and analytical layers.
• Conduct data profiling, lineage analysis, and quality checks to ensure models deliver trusted, consistent information.
• Document metadata, data dictionaries, and lineage across both transactional and analytical domains.
• Apply data governance and compliance best practices to meet regulatory requirements (HIPAA, SOX, GDPR, etc.)

• Bachelor's degree in Computer Science, Information Systems, or related field.
• 7+ years of technical and professional experience.
• 5+ years of hands‑on data modeling and database design experience, ideally in healthcare.
• Experience in FHIR (Fast Healthcare Interoperability Resources) and HL7 standards for transactional healthcare data preferred.
• Strong knowledge of analytical modeling (dimensional/star schema, Data Vault, warehouse/lakehouse environments).
• Experience with ETL/ELT processes and modern data pipeline development.
• Familiarity with data governance, lineage, and compliance requirements in healthcare.
• Strong analytical and problem‑solving skills with excellent attention to detail.

• Experience with cloud‑based healthcare data platforms (Azure, GCP, AWS, Databricks, Snowflake, etc.).
• Working knowledge of modern data catalogs, metadata tools, and security frameworks.
• Ability to balance operational and analytical priorities in data design.
• Collaborative mindset with the…