Data Engineer

Key Responsibilities

• Data Pipeline Development:
• Design, develop, and maintain scalable data pipelines using Databricks, Azure Data Factory, and other ETL tools.
• Optimize data workflows for efficient ingestion, transformation, and delivery of data from various sources.

Data Modeling And Storage

• Create and maintain data models and schemas tailored to analytics and business intelligence needs.
• Manage and optimize SQL Server databases and ensure data consistency, security, and accessibility.
• Data Integration:Work with diverse datasets, including structured and unstructured data, and integrate data from
• multiple sources .
• Ensure compliance with healthcare data standards, such as HL7, FHIR, and HIPAA.

Data Analysis And Reporting

• Leverage tools like Power BI, Tableau, and Qliksense to create interactive dashboards and visualizations
• for real-time insights.
• Collaborate with stakeholders to gather requirements and deliver actionable insights that address
• business and clinical needs.

Advanced Analytics

• Utilize Python, SQL, PySpark, and Spark SQL for advanced data processing, analysis, and predictive
• modeling.
• Support machine learning initiatives by preparing and processing large datasets for modeling.