AWS Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Data Engineer, remote in Virginia, with a contract length of "unknown" and a pay rate of "unknown." Key skills include AWS Glue, Python, API development, and AWS certification. Experience in clinical data processing is preferred.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
-
🗓️ - Date discovered
August 23, 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
Virginia, United States
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🧠 - Skills detailed
#Python #Cloud #Data Processing #Deployment #Data Lake #AWS Glue #S3 (Amazon Simple Storage Service) #PySpark #Compliance #Infrastructure as Code (IaC) #Data Engineering #Spark (Apache Spark) #"ETL (Extract #Transform #Load)" #API (Application Programming Interface) #AWS (Amazon Web Services)
Role description
Role- Data Engineer
Location- Virginia-USA (Remote)
Must-Have Skills:
• AWS Glue & Python: Strong experience in developing ETL pipelines using AWS Glue with Python (PySpark or Python shell jobs).
• API Development: Proven experience in writing and maintaining APIs to access and manage data in a Data Lake environment.
• Infrastructure as Code (IaC): Proficient in using AWS CDK (Cloud Development Kit) for deploying infrastructure components.
• CI/CD: Experience in building and managing deployment pipelines using AWS CodePipeline, CodeBuild, and related tools.
• AWS Certification
Preferred Qualifications:
• Domain Expertise: Background in clinical or medical imaging data processing and compliance (e.g., DICOM, PACS systems, HIPAA considerations).
• Data Lake Architecture: Understanding of Data Lake design patterns, Lake Formation, Glue Catalog, and S3 best practices.
Role- Data Engineer
Location- Virginia-USA (Remote)
Must-Have Skills:
• AWS Glue & Python: Strong experience in developing ETL pipelines using AWS Glue with Python (PySpark or Python shell jobs).
• API Development: Proven experience in writing and maintaining APIs to access and manage data in a Data Lake environment.
• Infrastructure as Code (IaC): Proficient in using AWS CDK (Cloud Development Kit) for deploying infrastructure components.
• CI/CD: Experience in building and managing deployment pipelines using AWS CodePipeline, CodeBuild, and related tools.
• AWS Certification
Preferred Qualifications:
• Domain Expertise: Background in clinical or medical imaging data processing and compliance (e.g., DICOM, PACS systems, HIPAA considerations).
• Data Lake Architecture: Understanding of Data Lake design patterns, Lake Formation, Glue Catalog, and S3 best practices.
