Data Engineer (AWS)

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 high-quality data solutions.


• Follow DevOps, security, and coding standards throughout the engagement.

Required Skills

• Bachelor’s degree in computer science or a related discipline.


• With around 3 plus years 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, including data lakes, IAM, S3, CloudWatch, and monitoring.

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