AWS Data Engineer-AWS data services: Amazon S3, AWS Glue, Amazon Redshift,

Rapsys Technologies Pte Ltd.; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

Rapsys Technologies Pte Ltd. in Singapore is seeking an AWS Data Engineer to design, build, and optimize data solutions using S3, Glue, Redshift, and related AWS services. You will shape data pipelines, governance, and analytics capabilities to drive business insights.

Join a fast-paced team in Singapore, contributing to end-to-end data lakehouse architecture, ingestion pipelines, and cost-optimized deployments on AWS.

Qualifications

• 3–5 years of experience in data engineering or cloud infra roles.
• Hands-on with core AWS data services: S3, Glue, Redshift, Lambda, Kinesis, Step Functions, EventBridge, AppFlow, Lake Formation.
• Strong SQL skills and scripting (Python or Scala).
• Experience designing Data Lake or Lakehouse architectures.
• Knowledge of data governance, cataloging, and metadata management.
• Experience with batch and streaming data processing patterns.
• AWS Data Engineer certification or Solutions Architect certification (or equivalent).

Responsibilities

• Architecture & Design: Design end-to-end AWS Data Lake/Lakehouse layers and governance standards.
• Development & Deployment: Build data ingestion pipelines with AWS Glue, Lambda, Step Functions, EventBridge, and API Gateway.
• Data Transformation: Create batch/stream processing workflows with AWS Glue and Redshift.
• Security & Governance: Enforce data security policies with Lake Formation and IAM.
• Maintenance & Operations: Monitor platform health and optimize performance and cost on AWS.

Skills

SQL

Python/Scala

AWS data services

Education

AWS Data Engineer Certification (Associate) or Solutions Architect

Tools

Amazon S3

AWS Glue

Amazon Redshift

AWS Lambda

Amazon Kinesis

AWS Step Functions

Amazon EventBridge

AWS AppFlow

AWS Lake Formation

Job description

We're Hiring: AWS Data Engineer!

We are searching for a skilled AWS Data Engineer to join our team in Singapore. If you have hands-on experience with Amazon S3, AWS Glue, and Amazon Redshift, and thrive in a fast-paced environment, we want to hear from you! Bring your expertise to help us design, build, and optimize data solutions that drive business insights.

Location: Singapore, Singapore

Work Mode: Work from Office

Role: AWS Data Engineer

What You'll Do:

Key Responsibilities

• Architecture & Design
  • Design and architect the end-to-end AWS Data Lake and Lakehouse solution, including Landing Zone, Transformed Zone, and Curated/Consumption Zone layers
  • Define and govern data architecture standards, patterns, and best practices across the platform
  • Architect reusable data ingestion pipelines supporting REST APIs, JDBC databases, S3 file uploads, and SaaS connectors (e.g. Salesforce via AWS AppFlow)
  • Design data storage strategies including hot, warm, and cold storage tiers, encryption, and data lifecycle policies
• Development & Deployment
  • Develop and deploy data ingestion pipelines using AWS Glue, Lambda, StepFunctions, EventBridge, and API Gateway
  • Build and maintain data transformation workflows (batch and streamprocessing) using AWS Glue and Amazon Redshift
  • Implement orchestration, monitoring, logging, and notification frameworks for pipeline operations
  • Develop and maintain the AWS Glue Data Catalogue, including schema evolution tracking and metadata tagging
• Security & Governance
  • Configure and enforce data security policies using AWS Lake Formation, IAM, and Secrets Manager
  • Implement granular access controls at database, table, and column levels
  • Ensure compliance with data classification, retention, and audit requirements
  • Support data quality frameworks and observability monitoring
• Maintenance & Operations
  • Monitor platform health, performance, and pipeline reliability
  • Troubleshoot and resolve data pipeline failures and data quality issues
  • Maintain documentation for architecture decisions, pipeline configurations, and operational runbooks
  • Continuously optimise platform performance and cost efficiency on AWS

Requirements

• Essential
  • Minimum 3 to 5 years of experience in data engineering, data architecture, orcloud infrastructure roles
  • Hands-on expertise with core AWS data services: Amazon S3, AWS Glue, AmazonRedshift, AWS Lambda, Amazon Kinesis, AWS Step Functions, Amazon EventBridge,AWS AppFlow, AWS Lake Formation
  • Strong proficiency in SQL and at least one scripting language (Python orScala)
  • Experience designing and implementing Data Lake or Lakehouse architectures
  • Solid understanding of data governance, data cataloguing, and metadatamanagement
  • Experience with batch and streaming data processing patterns
  • AWS Certified Data Engineer – Associate or AWS Certified Solutions Architectcertification (or equivalent)
• Preferred
  • Experience integrating with Tableau or similar BI visualisation tools viaAmazon Redshift or S3
  • Familiarity with MLOps frameworks and AI/ML model deployment on AWS SageMaker
  • Experience with Salesforce data integration using AWS AppFlow
  • Knowledge of Change Data Capture (CDC) and incremental data load patterns
  • Prior experience in a government or public sector data environment