Description We are seeking an experienced
Clinical Data Architect / Data Management Specialist to support the design, integration, cleansing, and processing of clinical data across multiple healthcare data sources. This role will focus on developing scalable data frameworks, establishing data standards, and transforming disparate healthcare data into a cohesive longitudinal data model to support analytics, reporting, and operational needs.
Requirements Key Responsibilities
- Design and maintain conceptual and logical data models for clinical data domains.
- Analyze and identify common data elements across multiple source systems.
- Develop and implement strategies for integrating data from disparate healthcare systems into a unified longitudinal framework.
- Coordinate data extraction, transfer, and integration activities with source systems and stakeholders.
- Define, develop, and implement data cleansing, validation, and processing routines to ensure data quality and integrity.
- Support ongoing data governance, data standardization, and master data management initiatives.
- Collaborate with technical, clinical, and business teams to ensure alignment of data architecture and reporting requirements.
- Create documentation for data models, transformation processes, and integration workflows.
Required Qualifications
- Bachelor's degree in Information Technology, Computer Science, Health Informatics, Data Science, or a related field, or equivalent work experience.
- 5+ years of experience in Data Architecture and Data Processing.
- 3+ years of experience working with Oracle Health (Cerner) healthcare data platforms.
- Experience designing and supporting large-scale healthcare or clinical data environments.
- Strong understanding of data integration, ETL processes, data validation, and data quality management.
Preferred Qualifications
- 5+ years of experience with Python for data processing and automation.
- 2+ years of experience with Google BigQuery.
- 2+ years of experience with Google Cloud Platform (Google Cloud Platform) infrastructure and services.
- Experience working with healthcare, clinical, or public health data.
- Knowledge of longitudinal data models and enterprise data architecture best practices.
Key Skills
- Data Architecture
- Clinical Data Management
- Data Integration & ETL
- Data Cleansing & Data Quality
- Oracle Health (Cerner)
- Python
- Google BigQuery
- Google Cloud Platform (Google Cloud Platform)
- Healthcare Data Analytics
- Data Modeling & Governance
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