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

Tap Growth ai; Singapore; On-site; SGD 100,000 - 150,000; Full time

Job summary

Tap Growth ai in Singapore is hiring an AWS Data Engineer to design and build data lakehouse solutions on AWS. You will craft end-to-end pipelines using S3, Glue, Redshift, Lambda, and more to drive business insights.

The role requires 3–5 years in data engineering, strong SQL and Python/Scala, and familiarity with governance, security, and cost optimization on AWS. Office-based in Singapore.

Qualifications

• 3–5 years of data engineering or cloud infrastructure experience.
• Hands-on with core AWS data services listed above.
• Strong SQL and scripting in Python or Scala.
• Experience designing Data Lake or Lakehouse architectures.
• Knowledge of data governance, cataloguing and metadata management.
• AWS Data Engineer – Associate or Solutions Architect cert (or equivalent).

Responsibilities

• Design end-to-end AWS Data Lake/Lakehouse architecture including landing, transformed, and curated zones.
• Develop and deploy data ingestion pipelines using AWS Glue, Lambda, Step Functions and API Gateway.
• Build and maintain batch and streaming ETL/ELT workflows with AWS Glue and Redshift.
• Implement orchestration, monitoring, logging, and alerting for data pipelines.
• Maintain and evolve the AWS Glue Data Catalogue with schema evolution and tagging.
• Enforce data security via Lake Formation, IAM, and Secrets Manager.
• Optimize platform performance and cost efficiency on AWS.

Skills

SQL

Python

Scala

Data Lake/Lakehouse

Data governance

Tools

Amazon S3

AWS Glue

Amazon Redshift

AWS Lambda

AWS Step Functions

EventBridge

API Gateway

IAM

Secrets Manager

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

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