Senior Data Engineer / Data Architect (Remote and W2)

🌍 Remote, USA 🎯 Full-time 🕐 Posted Recently

Job Description

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.

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.

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.

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