AWS Data Engineer

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 AWS Lambda.
• Write clean, efficient, and maintainable Python/PySpark code following engineering best practices.
• Provision and manage cloud infrastructure using Terraform (Infrastructure as Code).
• Implement and maintain CI/CD pipelines to automate code deployment, testing, and infrastructure changes.
• Monitor, troubleshoot, and optimize data pipelines for performance, reliability, and cost efficiency.
• Collaborate with business stakeholders to deliver data solutions.
• Follow DevOps, security, and coding standards throughout the engagement.

Required Skills

• Strong hands‑on experience with PySpark and Python for data engineering.
• Experience developing ETL pipelines using AWS Glue.
• Proficiency with AWS Step Functions for workflow orchestration.
• Experience building serverless solutions using AWS Lambda.
• Hands‑on experience with Terraform for Infrastructure as Code (IaC).
• Experience implementing CI/CD pipelines using tools such as GitLab, GitHub Actions, Jenkins, or similar.
• Good understanding of AWS services, data lakes, IAM, S3, CloudWatch, and monitoring.