Senior Data Engineer / Data Architect (Remote and W2)
Senior Data Engineer / Data Architect (Remote and W2)
Key Responsibilities:
• Design & Architecture: Architect and design large-scale data systems, leveraging cloud technologies such as Azure Databricks, Snowflake, AWS, and Azure Synapse for healthcare data ecosystems.
• ETL/ELT Pipelines: Build and optimize data pipelines using dbt, Apache Airflow, Azure Data Factory, and Python/PySpark to manage large volumes of healthcare data.
• Healthcare Data Integration: Integrate data from systems such as Epic (Clarity, Caboodle, Tapestry), FHIR, HL7, and claims data for analysis and AI/ML models.
• AI & Machine Learning: Implement AI-driven analytics, predictive modeling, and machine learning workflows to automate healthcare data processes and generate actionable insights.
• Governance & Compliance: Implement and manage data governance frameworks ensuring HIPAA and GDPR compliance.
• Collaboration & Mentorship: Collaborate with cross-functional teams and mentor junior engineers to ensure the success of data engineering initiatives.
• Reporting & Business Intelligence: Develop dashboards using tools like Power BI, Qlik Sense, and DOMO, ensuring that data insights are actionable and meet business needs.
• Optimization & Performance Tuning: Continuously monitor and optimize data systems for performance, reliability, and scalability.
Key Skills & Experience:
• Experience: 10+ years of experience in data engineering or data architecture, particularly in the healthcare or large-scale data systems sector.
• Healthcare Systems: Strong knowledge of healthcare data systems, including Epic, FHIR, HL7, claims data, and Revenue Cycle Management (RCM).
• Cloud Platforms: Expertise in Azure Databricks, Snowflake, AWS (S3, Glue, Lambda, Redshift), and Azure Synapse.
• Data Engineering Tools: Hands-on experience with dbt, Apache Airflow, Azure Data Factory, Python, PySpark, and other data engineering tools.
• Machine Learning: Experience with AI-driven analytics, predictive modeling, and tools like Azure AI Foundry and NLP.
• BI & Reporting: Proficiency in Power BI, Qlik Sense, DOMO, and other BI/reporting tools.
• Compliance: Knowledge of HIPAA, GDPR, and other healthcare data compliance standards.
• Team Collaboration: Excellent communication skills and ability to work in a collaborative, remote environment.
• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Preferred Qualifications:
• Certifications in Epic Systems or related healthcare platforms.
• Experience with Delta Lake, Unity Catalog, and Lakehouse Architecture.
• Expertise in AI, machine learning, and predictive analytics techniques.
• Familiarity with large-scale healthcare data integration and governance frameworks.
Apply Now
Apply Now
Key Responsibilities:
• Design & Architecture: Architect and design large-scale data systems, leveraging cloud technologies such as Azure Databricks, Snowflake, AWS, and Azure Synapse for healthcare data ecosystems.
• ETL/ELT Pipelines: Build and optimize data pipelines using dbt, Apache Airflow, Azure Data Factory, and Python/PySpark to manage large volumes of healthcare data.
• Healthcare Data Integration: Integrate data from systems such as Epic (Clarity, Caboodle, Tapestry), FHIR, HL7, and claims data for analysis and AI/ML models.
• AI & Machine Learning: Implement AI-driven analytics, predictive modeling, and machine learning workflows to automate healthcare data processes and generate actionable insights.
• Governance & Compliance: Implement and manage data governance frameworks ensuring HIPAA and GDPR compliance.
• Collaboration & Mentorship: Collaborate with cross-functional teams and mentor junior engineers to ensure the success of data engineering initiatives.
• Reporting & Business Intelligence: Develop dashboards using tools like Power BI, Qlik Sense, and DOMO, ensuring that data insights are actionable and meet business needs.
• Optimization & Performance Tuning: Continuously monitor and optimize data systems for performance, reliability, and scalability.
Key Skills & Experience:
• Experience: 10+ years of experience in data engineering or data architecture, particularly in the healthcare or large-scale data systems sector.
• Healthcare Systems: Strong knowledge of healthcare data systems, including Epic, FHIR, HL7, claims data, and Revenue Cycle Management (RCM).
• Cloud Platforms: Expertise in Azure Databricks, Snowflake, AWS (S3, Glue, Lambda, Redshift), and Azure Synapse.
• Data Engineering Tools: Hands-on experience with dbt, Apache Airflow, Azure Data Factory, Python, PySpark, and other data engineering tools.
• Machine Learning: Experience with AI-driven analytics, predictive modeling, and tools like Azure AI Foundry and NLP.
• BI & Reporting: Proficiency in Power BI, Qlik Sense, DOMO, and other BI/reporting tools.
• Compliance: Knowledge of HIPAA, GDPR, and other healthcare data compliance standards.
• Team Collaboration: Excellent communication skills and ability to work in a collaborative, remote environment.
• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Preferred Qualifications:
• Certifications in Epic Systems or related healthcare platforms.
• Experience with Delta Lake, Unity Catalog, and Lakehouse Architecture.
• Expertise in AI, machine learning, and predictive analytics techniques.
• Familiarity with large-scale healthcare data integration and governance frameworks.
Apply Now
Apply Now