Senior Data Engineer​/Data Architect; Remote and W2

Senior Data Engineer / Data Architect (Remote and W2)

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This role is for a Senior Data Engineer/Data Architect (Remote, W2) with a contract length of "X months" and a pay rate of "$X/hour." Requires 10+ years in data engineering, expertise in healthcare data systems, and proficiency in cloud platforms and data engineering tools.

• 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.
• 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.

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