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

RAPSYS TECHNOLOGIES PTE LTD; Singapore; On-site; SGD 120,000 - 180,000; 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, AWS Glue, and Redshift.

You will own end-to-end data lake/lakehouse architectures, ingest pipelines, security governance, and cost-efficient operations, collaborating with cross-functional teams.

Qualifications

• Minimum 3 to 5 years of experience in data engineering, data architecture, or cloud infrastructure roles
• Hands-on expertise with core AWS data services: Amazon S3, AWS Glue, Amazon Redshift, 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 or Scala)
• Experience designing and implementing Data Lake or Lakehouse architectures
• Solid understanding of data governance, data cataloguing, and metadata management
• Experience with batch and streaming data processing patterns
• AWS Certified Data Engineer - Associate or AWS Certified Solutions Architect certification (or equivalent)

Responsibilities

• Design and architect end-to-end AWS Data Lake and Lakehouse solution layers
• Define and govern data architecture standards, patterns, and best practices
• Architect reusable data ingestion pipelines for REST APIs, JDBC, S3 uploads, and SaaS connectors
• Design data storage strategies with hot, warm, and cold tiers and lifecycle policies
• Develop and deploy data ingestion pipelines using AWS Glue, Lambda, Step Functions, EventBridge, API Gateway
• Build and maintain data transformation workflows (batch and streaming) using AWS Glue and Redshift
• Implement security policies using Lake Formation, IAM, and Secrets Manager
• Monitor, optimize, and document architecture decisions and pipeline configurations

Skills

SQL

Python/Scala

Data architecture

AWS data services

Data governance

Batch/stream processing

Education

AWS Certification (Data Engineer Associate / Solutions Architect)

Tools

AWS Glue

AWS Lambda

AWS Step Functions

Amazon Kinesis

AWS AppFlow

AWS Lake Formation

Amazon Redshift

S3

Job description

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.

What You'll Do:

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, Step Functions, EventBridge, and API Gateway
• Build and maintain data transformation workflows (batch and stream processing) 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, or cloud infrastructure roles
• Hands-on expertise with core AWS data services: Amazon S3, AWS Glue, Amazon Redshift, 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 or Scala)
• Experience designing and implementing Data Lake or Lakehouse architectures
• Solid understanding of data governance, data cataloguing, and metadata management
• Experience with batch and streaming data processing patterns
• AWS Certified Data Engineer - Associate or AWS Certified Solutions Architect certification (or equivalent)

Preferred

• Experience integrating with Tableau or similar BI visualisation tools via Amazon 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