AWS Data Engineer

Cognizant Technology Solutions Asia Pacific Pte. Ltd.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Cognizant Technology Solutions Asia Pacific Pte. Ltd. is seeking a data engineering professional to design, build, and optimize scalable data pipelines on AWS using PySpark and Python. You will implement ETL/ELT workflows, serverless solutions, and IaC with Terraform while maintaining robust CI/CD processes.

Role focuses on data lake data engineering, cost-aware operations, and collaboration with business stakeholders to deliver secure, scalable data solutions in a cloud-first environment.

Qualifications

• Hands-on PySpark and Python data engineering experience.
• Experience ETL pipelines with AWS Glue.
• AWS Step Functions and Lambda/serverless development.
• Terraform IaC and CI/CD pipelines with GitLab/GitHub/Jenkins.

Responsibilities

• Design and maintain scalable data pipelines using PySpark on AWS.
• Build ETL/ELT workflows with AWS Glue and Step Functions.
• Develop serverless apps and automation with AWS Lambda.
• Write clean Python/PySpark code following best practices.
• Provision and manage cloud infrastructure with Terraform.
• Implement CI/CD pipelines to automate deployments and tests.
• Monitor and optimize data pipelines for performance and cost.
• Collaborate with stakeholders and follow DevOps standards.

Skills

PySpark

Python

AWS Services

CI/CD Practices

Workflow orchestration

Tools

Terraform IaC

GitHub Actions

GitLab

Jenkins

AWS Step Functions

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.