PGC Digital (America) Inc: CMMI Level 3 Company
Lead AWS Data Engineer with DynamoDB Exp
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Lead AWS Data Engineer with DynamoDB experience, offering a contract length of "unknown" and a pay rate of "unknown." Key skills include Python, AWS Glue, DynamoDB, SQL, and experience with CI/CD tools.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
520
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🗓️ - Date
March 17, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Juno Beach, FL
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🧠 - Skills detailed
#Triggers #Terraform #API (Application Programming Interface) #Data Modeling #SQL (Structured Query Language) #AWS (Amazon Web Services) #IAM (Identity and Access Management) #Infrastructure as Code (IaC) #AWS Glue #Cloud #PySpark #Lambda (AWS Lambda) #Data Pipeline #POSTMAN #Automation #Data Processing #GIT #Spark (Apache Spark) #Data Engineering #Version Control #DynamoDB #S3 (Amazon Simple Storage Service) #Python #"ETL (Extract #Transform #Load)"
Role description
Job Description
• Hands on data engineering experience with proven track record of building production data pipelines
• Expert level proficiency in Python for data processing, ETL development, and automation (PySpark)
• Deep experience with AWS Glue including job development, crawlers, triggers, and workflow orchestration
• Strong expertise in DynamoDB data modeling, capacity planning, streams, and performance optimization
• Solid understanding of AWS ecosystem: S3, Lambda, Step Functions, CloudWatch, IAM, KMS, Kinesis
• Proficiency with Postman for API development, testing, and collaboration
• Strong SQL skills and understanding of data warehousing principles
• Experience with version control (Git), CI/CD tools, and infrastructure as code (CloudFormation/Terraform)
Job Description
• Hands on data engineering experience with proven track record of building production data pipelines
• Expert level proficiency in Python for data processing, ETL development, and automation (PySpark)
• Deep experience with AWS Glue including job development, crawlers, triggers, and workflow orchestration
• Strong expertise in DynamoDB data modeling, capacity planning, streams, and performance optimization
• Solid understanding of AWS ecosystem: S3, Lambda, Step Functions, CloudWatch, IAM, KMS, Kinesis
• Proficiency with Postman for API development, testing, and collaboration
• Strong SQL skills and understanding of data warehousing principles
• Experience with version control (Git), CI/CD tools, and infrastructure as code (CloudFormation/Terraform)
