AWS Data Engineer

Key Responsibilities

. Design, develop, and maintain scalable data pipelines using PySparkon AWS.

. Build and orchestrate ETL/ELT workflows using AWS Glueand AWS Step Functions.

. Develop serverless applications and automation using AWSLambda.

. Write clean, efficient, and maintainable Python/PySpark codefollowing engineering best practices.

. Provision and manage cloud infrastructure using Terraform(Infrastructure as Code).

. Implement and maintain CI/CD pipelines to automate codedeployment, testing, and infrastructure changes.

. Monitor, troubleshoot, and optimize data pipelines forperformance, reliability, and cost efficiency.

. Collaborate with business stakeholders to deliver datasolutions.

. Follow DevOps, security, and coding standards throughout theengagement.

Required Skills

. Strong hands-on experience with PySpark and Python fordata engineering.

. Experience developing ETL pipelines using AWS Glue.

. Proficiency with AWS Step Functions for workfloworchestration.

. Experience building serverless solutions using AWS Lambda.

. Hands-on experience with Terraform for Infrastructure asCode (IaC).

. Experience implementing CI/CD pipelines using tools suchas GitLab, GitHub Actions, Jenkins, or similar.

. Good understanding of AWS services, data lakes, IAM, S3,CloudWatch, and monitoring.