AWS Data Engineer-AWS data services: Amazon S3, AWS Glue, Amazon Redshift,
Posted 1
view
Summary
AWS Data Engineer based in Singapore (office-based) who designs, builds, and operates end-to-end data lake/lakehouse pipelines — ingestion, transformation, orchestration, security, and governance — using Amazon S3, AWS Glue, Amazon Redshift, Lambda, and related AWS data services.
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
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 practicesacross the platform
- Architect reusable data ingestion pipelines supporting REST APIs, JDBCdatabases, S3 file uploads, and SaaS connectors (e.g. Salesforce via AWSAppFlow)
- 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 forpipeline operations
- Develop and maintain the AWS Glue Data Catalogue, including schema evolutiontracking 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