Data Engineer - AWS/Pyspark

Vui Systems Pte Ltd; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Vui Systems Pte Ltd is seeking a data engineer to design, develop, and maintain scalable data pipelines on AWS using PySpark and Python. You will build ETL/ELT workflows with AWS Glue and Step Functions, develop serverless applications with Lambda, and manage cloud infrastructure with Terraform.

You will implement CI/CD pipelines, monitor pipelines for performance and cost, and collaborate with stakeholders to deliver data solutions while upholding DevOps and security standards.

Qualifications

• 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.

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.

Skills

PySpark

Python

Tools

AWS Glue

AWS Step Functions

AWS Lambda

Terraform

GitLab

GitHub Actions

Jenkins

Job description

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.