Codebase Inc

AWS Data Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Data Engineer with a long-term contract, offering remote work. Key skills include Python, SQL, AWS services (Glue, Redshift), and CI/CD tools. Requires a Bachelor's degree and 5+ years of data engineering experience. AWS certification is a plus.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
January 29, 2026
πŸ•’ - Duration
Unknown
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🏝️ - Location
Remote
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
United States
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🧠 - Skills detailed
#Lambda (AWS Lambda) #Programming #Observability #AWS Glue #SQL (Structured Query Language) #Redshift #Automated Testing #Scripting #Cloud #Data Integration #Deployment #Data Engineering #Data Quality #Python #Terraform #Automation #Data Pipeline #Monitoring #S3 (Amazon Simple Storage Service) #"ETL (Extract #Transform #Load)" #Shell Scripting #Computer Science #Scala #Jenkins #AWS (Amazon Web Services)
Role description
Position :- AWS Data Engineer Location: Remote Duration: Long term Role Summary: The Data Engineer will build and maintain secure, scalable, and automated data pipelines to support the ingestion, transformation, and curation of data products. This role will focus on implementing CI/CD pipelines, automated testing, and monitoring solutions. Required Skills β€’ Programming: Proficiency in Python, SQL, and shell scripting. β€’ AWS Expertise: Hands-on experience with AWS services (Glue, Redshift, S3, Lambda, CloudWatch). β€’ Automation: Experience with CI/CD tools (Terraform, Jenkins, AWS CodePipeline). β€’ Data Integration: Strong knowledge of ETL/ELT processes and frameworks. β€’ Soft Skills: Strong problem-solving, collaboration, and communication skills. Qualifications β€’ Bachelor’s degree in Computer Science, Data Engineering, or related field. β€’ 5+ years of experience in data engineering and pipeline development. β€’ AWS Certified Data Analytics or AWS Certified Developer is a plus Key Responsibilities β€’ Data Pipelines: Develop configuration-driven ingestion and transformation pipelines using AWS Glue, Lambda, and Redshift. β€’ Automation: Implement CI/CD pipelines for automated build, test, and deployment of data products. β€’ Testing: Establish automated test frameworks for schema validation, data quality, and performance testing. β€’ Monitoring: Set up monitoring and observability dashboards for product-level metrics (CloudWatch, custom metrics). β€’ Collaboration: Work with data modelers and architects to ensure alignment with business requirements.