EDI Data Engineer (Healthcare Domain)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an EDI Data Engineer in the healthcare domain, offering a contract position with a pay rate of "unknown." It requires 10+ years of experience, expertise in Python, AWS, and healthcare data, and strong leadership in data projects.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
-
🗓️ - Date discovered
July 12, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Remote
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Data Quality #Redshift #Shell Scripting #Spark (Apache Spark) #Python #Data Architecture #Scala #Scripting #SQL (Structured Query Language) #Data Lake #PySpark #Agile #BI (Business Intelligence) #Data Engineering #Data Pipeline #Airflow #S3 (Amazon Simple Storage Service) #Cloud #Informatica #AWS (Amazon Web Services) #Big Data #"ETL (Extract #Transform #Load)" #Lambda (AWS Lambda) #Bash #Automation #Data Processing
Role description
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Role: EDI Data Engineer – Healthcare Domain
Location: NYC, NY & Canada (Remote)
Job Type: Contract
Note: Need minimum 10+ years experience and recent lead expertise
Summary
• The Senior Data Engineer designs and leads scalable data architectures and pipelines to support analytics and business intelligence.
• This role focuses on data optimization, workflow automation, and ensuring reliable data operations in a cloud-based environment
Minimum Qualifications
• 8+ years of IT experience, with 5+ years in:
• Python, PySpark, and SQL for big data processing
• Data lakes (Iceberg format), ETL (Informatica), and data quality
• AWS services: S3, Glue, Redshift, Lambda, EMR, Airflow, Postgres
• BASH/Shell scripting
• Experience with healthcare data and leading data teams
• Agile development experience
Responsibilities
• Design and maintain scalable data pipelines and architectures
• Lead data projects and ensure best practices
• Optimize data systems for analytics and reporting
• Ensure data quality and system reliability in production environments
