AWS Data Engineer

Visa Hunt; Singapore; On-site; SGD 110,000 - 170,000; Full time

Job summary

Visa Hunt in Singapore seeks an experienced data engineer to design and maintain scalable data pipelines using PySpark on AWS. You will work with data lakes, governance, and modernization initiatives, collaborating with business stakeholders to deliver reliable data solutions.

The role emphasizes hands-on development in Python, ETL/ELT patterns, and infrastructure as code with Terraform, alongside CI/CD automation and monitoring to ensure cost-efficient, compliant data pipelines.

Qualifications

• Hands-on PySpark and Python for data engineering.
• ETL pipelines with AWS Glue.
• Workflow orchestration with AWS Step Functions.
• Serverless solutions with AWS Lambda.
• Terraform IaC for cloud infra.
• CI/CD pipelines with GitLab, GitHub Actions or Jenkins.
• Good understanding of AWS services, data lakes, IAM, S3, CloudWatch.

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

Skills

PySpark

Python

AWS Glue

Step Functions

Lambda

Terraform

CI/CD

AWS services

Data lakes

Tools

GitLab

GitHub Actions

Jenkins

Job description

This role requires strong data Engineering& analysis expertise across SQL, Data modelling, DBT, Airflow, and Lakehouse/data lake architecture, with hands‑on experience querying large-scale distributed datasets directly from data lakes.

Banking/financial services experience, exposure to ledger/ transactional/ regulatory data, support for migration/modernization program, familiarity, with data governance / metadata. regulatory controls.

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.