HMG AMERICA LLC
AWS Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Data Engineer with a contract length of "unknown" and a pay rate of "unknown." It requires strong experience in PySpark, Apache Iceberg, and AWS-native architectures, focusing on scalable data platforms and handling large datasets.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
June 18, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Remote
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#Data Lake #PySpark #Data Pipeline #S3 (Amazon Simple Storage Service) #Datasets #Terraform #Spark (Apache Spark) #AI (Artificial Intelligence) #Data Processing #Data Architecture #Apache Iceberg #"ETL (Extract #Transform #Load)" #Data Engineering #Monitoring #Scala #AWS (Amazon Web Services)
Role description
Job Title: AWS Data Engineer
Location: Remote USA
We are looking for a highly skilled AWS Data Engineer with strong experience in PySpark, Apache Iceberg, and AWS-native data architectures. The ideal candidate should have hands-on expertise building scalable and high-performance data platforms handling millions of rows of data.
Required Skills:
• Strong hands-on experience with PySpark
• Strong hands-on experience with Apache Iceberg + Terraform
• Experience with EMR + Glue
• Deep understanding of AWS native architecture
• Experience designing scalable and performant applications/data pipelines
• Knowledge of data lake and distributed processing concepts
• Experience handling large-scale datasets and optimization techniques
Good to Have:
• Exposure to Agentic Workflows
• Experience with modern AI/data engineering ecosystems
Responsibilities:
• Build and optimize scalable ETL/data pipelines using PySpark
• Design AWS-based data engineering solutions using EMR, Glue, S3, Iceberg, etc.
• Improve performance and scalability for large-scale data processing systems
• Collaborate with architects, analysts, and engineering teams on data initiatives
• Ensure reliability, monitoring, and best practices across data platforms
Extracted Text from Image:
• EMR + Glue
• Strong hands on with PySpark
• Strong hands-on with Iceberg
• Understand internals of AWS native architecture
• Worked with design principles handling millions of rows and building performant applications
• Good to have exposure to agentic workflows
Job Title: AWS Data Engineer
Location: Remote USA
We are looking for a highly skilled AWS Data Engineer with strong experience in PySpark, Apache Iceberg, and AWS-native data architectures. The ideal candidate should have hands-on expertise building scalable and high-performance data platforms handling millions of rows of data.
Required Skills:
• Strong hands-on experience with PySpark
• Strong hands-on experience with Apache Iceberg + Terraform
• Experience with EMR + Glue
• Deep understanding of AWS native architecture
• Experience designing scalable and performant applications/data pipelines
• Knowledge of data lake and distributed processing concepts
• Experience handling large-scale datasets and optimization techniques
Good to Have:
• Exposure to Agentic Workflows
• Experience with modern AI/data engineering ecosystems
Responsibilities:
• Build and optimize scalable ETL/data pipelines using PySpark
• Design AWS-based data engineering solutions using EMR, Glue, S3, Iceberg, etc.
• Improve performance and scalability for large-scale data processing systems
• Collaborate with architects, analysts, and engineering teams on data initiatives
• Ensure reliability, monitoring, and best practices across data platforms
Extracted Text from Image:
• EMR + Glue
• Strong hands on with PySpark
• Strong hands-on with Iceberg
• Understand internals of AWS native architecture
• Worked with design principles handling millions of rows and building performant applications
• Good to have exposure to agentic workflows
