مهندس بيانات

Key Responsibilities Design, build, and maintain data pipelines that extract, transform, and load data from source systems into reporting and analytics environments. Develop and maintain the data warehouse / data mart structure to support operational, clinical, financial, and population health reporting. Integrate data from multiple systems such as: HIS / EMR ERP / Finance HR systems Laboratory / Radiology / Pharmacy systems Manual and external data sources Clean, standardize, and validate data to improve data quality, consistency, and usability . Build and maintain reusable datasets for Power BI dashboards , KPI tracking, and automated reporting. Work with analysts and business stakeholders to translate reporting needs into structured data models. Support the development of: patient registries physician registries disease registries performance and KPI datasets Monitor pipeline performance, troubleshoot failures, and ensure timely data refresh. Document data sources, logic, definitions, and transformations clearly. Participate in data governance efforts, including master data standardization, metric definitions, and access controls. Ensure compliance with organizational policies related to data privacy, security, and confidentiality . Required Qualifications Bachelor’s degree in: Computer Science Data Engineering Information Systems Software Engineering or related field Proven experience in data engineering, ETL development, or database development Strong SQL skills Experience with data integration and transformation tools Experience working with relational databases and large datasets Experience supporting BI/reporting environments Preferred Qualifications Experience in healthcare, hospital, or EMR/HIS data environments Experience with: Microsoft SQL Server Azure Data Factory SSIS Python Power BI backend support Familiarity with healthcare data domains such as visits, billing, orders, labs, diagnoses, procedures, and registries Understanding of data warehouse concepts such as: star schema fact and dimension tables data modeling data lineage Key Skills Strong SQL and database skills ETL / ELT pipeline development Data modeling Problem-solving and troubleshooting Attention to detail Documentation and organization Ability to work with both technical and non-technical stakeholders Understanding of data quality and governance principles Core Deliverables Reliable automated data pipelines Clean and validated reporting datasets Structured data models for dashboards and KPIs Better accessibility of data across departments Reduced manual reporting effort Improved readiness for enterprise analytics and value-based care initiatives