Actively looking for a Data engineer with AWS Glue and Redshift
Role: AWS Data Engineer
Location: 100% Remote
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.
Key Responsibilities:
Data Pipelines:
Develop configuration-driven ingestion and transformation pipelines using AWS Glue, Lambda, and Redshift.
Automation:
Implement CI/CD pipelines for automated build, test, and deployment of data products.
Testing:
Establish automated test frameworks for schema validation, data quality, and performance testing.
Monitoring:
Set up monitoring and observability dashboards for product-level metrics (CloudWatch, custom metrics).
Collaboration:
Work with data modelers and architects to ensure alignment with business requirements.
Required Skills:
Programming:
Proficiency in Python, SQL, and shell scripting.
AWS Expertise:
Hands-on experience with AWS services (Glue, Redshift, S3, Lambda, CloudWatch).
Automation:
Experience with CI/CD tools (Terraform, Jenkins, AWS CodePipeline).
Data Integration:
Strong knowledge of ETL/ELT processes and frameworks.
Soft Skills:
Strong problem-solving, collaboration, and communication skills.
Qualifications:
Bachelor s degree in computer science, Data Engineering, or related field.
5+ years of experience in data engineering and pipeline development.
AWS Certified Data Analytics or AWS Certified Developer is a plus.
Location: 100% Remote
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.
Key Responsibilities:
Data Pipelines:
Develop configuration-driven ingestion and transformation pipelines using AWS Glue, Lambda, and Redshift.
Automation:
Implement CI/CD pipelines for automated build, test, and deployment of data products.
Testing:
Establish automated test frameworks for schema validation, data quality, and performance testing.
Monitoring:
Set up monitoring and observability dashboards for product-level metrics (CloudWatch, custom metrics).
Collaboration:
Work with data modelers and architects to ensure alignment with business requirements.
Required Skills:
Programming:
Proficiency in Python, SQL, and shell scripting.
AWS Expertise:
Hands-on experience with AWS services (Glue, Redshift, S3, Lambda, CloudWatch).
Automation:
Experience with CI/CD tools (Terraform, Jenkins, AWS CodePipeline).
Data Integration:
Strong knowledge of ETL/ELT processes and frameworks.
Soft Skills:
Strong problem-solving, collaboration, and communication skills.
Qualifications:
Bachelor s degree in computer science, Data Engineering, or related field.
5+ years of experience in data engineering and pipeline development.
AWS Certified Data Analytics or AWS Certified Developer is a plus.