Data Engineer - AWS/Pyspark

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using PySpark on AWS.
• Build and orchestrate ETL/ELT workflows using AWS Glue and 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.