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AWS Data Engineer

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Onsite

AWS Data Engineer

RAPSYS TECHNOLOGIES PTE LTD

AWS Data Engineer

Skills

SQL QueriesData EngineeringTableauPythonAWS LambdaAmazon RedshiftMachine LearningAIScalaAWSSalesforceAWS KinesisCompliance

1 month ago

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Important information


Contract type:

Permanent

Location:

Singapore

Work mode:

Onsite

Published on:

7 September 2026

What they need


🌟 We're Hiring: AWS Data Engineer! 🌟

We are looking for a skilled AWS Data Engineer to join our dynamic team and help design, build, and maintain robust data pipelines on AWS. The ideal candidate will have hands-on experience in cloud-based data engineering, a passion for solving complex data challenges, and the ability to collaborate effectively with cross-functional teams.

📍 Location: Singapore, Singapore

⏰ Work Mode: Work from Office

💼 Role: AWS Data Engineer

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, 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

Keen to advance your career in cloud data engineering? 🚀 Apply now to join our innovative team!

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