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.