AWS Data Engineer: Lakehouse & Data Pipelines

Visa Hunt; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

Visa Hunt is seeking an AWS Data Engineer / Data Architect to design, build and maintain a modern AWS Data Lake and Lakehouse platform in Singapore. You will work on data ingestion, transformation, storage, security and governance, ensuring pipelines are reliable, scalable and cost-efficient.

Responsibilities include designing and developing AWS Data Lake and Lakehouse solutions, building data pipelines, and maintaining the AWS Glue Data Catalogue, with emphasis on data governance, metadata

Qualifications

• Must have 3–5 years of experience in Data Engineering, Data Architecture, Cloud Infrastructure or a related role.
• Strong hands-on experience with AWS data services and governance tools.
• Proficient in SQL and one or more programming languages (Python or Scala).

Responsibilities

• Design and develop AWS Data Lake and Lakehouse solutions.
• Build data pipelines using APIs, databases, files and SaaS platforms.
• Develop data ingestion and transformation workflows.
• Work with AWS Glue, S3, Redshift, Lambda and Step Functions.
• Manage data processing for both batch and streaming data.
• Maintain the AWS Glue Data Catalogue and data metadata.
• Implement data security and access controls.
• Monitor and troubleshoot data pipelines and data quality issues.
• Maintain technical documentation.

Skills

Data engineering

Data architecture

Cloud infrastructure

SQL

Python

Scala

Data governance

Data cataloguing

Streaming data processing

Batch data processing

AWS certifications

Tools

Amazon S3

AWS Glue

Amazon Redshift

AWS Lambda

AWS Step Functions

Amazon Kinesis

Amazon EventBridge

AWS AppFlow

AWS Lake Formation

Job description

Visa Hunt is seeking an AWS Data Engineer / Data Architect to design, build and maintain a modern AWS Data Lake and Lakehouse platform in Singapore. You will work on data ingestion, transformation, storage, security and governance, ensuring pipelines are reliable, scalable and cost-efficient.

Responsibilities include designing and developing AWS Data Lake and Lakehouse solutions, building data pipelines, and maintaining the AWS Glue Data Catalogue, with emphasis on data governance, metadata