

Codebase Inc
AWS Data Engineer
β - 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.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
Unknown
-
ποΈ - Date
January 29, 2026
π - Duration
Unknown
-
ποΈ - Location
Remote
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
United States
-
π§ - 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’ Bachelorβs 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.
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’ Bachelorβs 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.






