Healthcare Azure Data Architect Contract

Healthcare Azure Data Architect with specialization in oncology

Remote

We are seeking a highly skilled and experienced Healthcare Azure Data Architect with a specialization in oncology. The ideal candidate will have a strong background in real-time and batch data integration and analytics, and will play a pivotal role in designing and implementing data solutions that support our oncology initiatives.

Key Responsibilities:

Architectural Design: Design and develop scalable, robust, and secure data architectures on the Azure platform to support oncology research and clinical applications.
Data Integration: Implement real-time and batch data integration solutions to collect, process, and store data from various healthcare systems, including EHRs, laboratory systems, and clinical trial databases.
Analytics and Reporting: Develop advanced analytics and reporting solutions to provide actionable insights for oncology research and patient care.
Collaboration: Work closely with oncologists, data scientists, and other stakeholders to understand their data needs and translate them into technical requirements.
Data Governance: Establish and enforce data governance policies and procedures to ensure data quality, privacy, and compliance with healthcare regulations (e.g., HIPAA).
Performance Optimization: Optimize data pipelines and architectures for performance, scalability, and cost-efficiency.
Documentation: Create and maintain comprehensive documentation of data architectures, integration processes, and analytics solutions.
Qualifications:

Education: Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field. Advanced certifications in Azure and/or healthcare data management are a plus.
Experience:
Minimum of 5 years of experience in data architecture, with a focus on healthcare and oncology.
Proven experience in designing and implementing data solutions on the Azure platform.
Expertise in real-time data integration technologies (e.g., Azure Stream Analytics, Azure Event Hubs) and batch processing frameworks (e.g., Azure Data Factory, Apache Spark).
Technical Skills:
Proficiency in SQL, Python, and other relevant programming languages.
Deep understanding of data modeling, ETL processes, and data warehousing concepts.
Experience with Azure Data Lake, Azure Synapse Analytics, and other Azure data services.
Familiarity with healthcare data standards and protocols (e.g., HL7, FHIR).
Soft Skills:
Strong analytical and problem-solving skills.
Excellent communication and collaboration abilities.
Ability to work in a fast-paced, dynamic environment.
Preferred Qualifications:

Experience with machine learning and AI applications in healthcare.
Knowledge of oncology-specific data and research methodologies.
Experience with data visualization tools (e.g., Power BI).