Data Engineer (AWS, Central Location)
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Summary
A senior data engineer role in Singapore designing, building, and operating AWS-based enterprise data platforms — building ETL/ELT pipelines with Glue, Step Functions, Lambda, and S3, plus Iceberg/S3 Tables lakehouse solutions, data quality frameworks, and CI/CD with Terraform/CloudFormation, likely for a government-sector client.
Our client is looking for a
Senior Data Engineer
to design, build and operate enterprise-grade data platforms supporting analytics, data science and digital products. The role will contribute to data architecture, engineering standards and technical decision-making in a complex enterprise environment.
Responsibilities Design and implement scalable ETL/ELT data pipelines using AWS services including Glue, Step Functions, Lambda, and S3. Build and optimise data lakehouse solutions using Apache Iceberg or S3 Tables, including schema/partition evolution and ACID transactions. Develop automated data quality validation and monitoring frameworks to ensure data accuracy, completeness, and consistency. Develop production-quality code and deploy solutions using CI/CD and Infrastructure-as-Code tools such as Terraform or CloudFormation. Optimise solutions for performance, scalability, cost, and reliability. Collaborate with cross-functional teams, communicate technical solutions to non-technical stakeholders, and prepare documentation for handover to the Day 2 operations team.
Requirements Degree in Computer Science, Data Engineering, Information Systems, or a related discipline. 3–5 years of experience in data engineering, ETL/ELT development, or data platform roles. Strong hands-on experience with AWS and modern data engineering practices. Proficiency in Apache Iceberg or similar open table formats and data lakehouse architectures. Experience with data quality, governance, CI/CD, and Infrastructure-as-Code. Experience in a Government Commercial Cloud (GCC) environment is strongly preferred. AWS certifications such as AWS Certified Data Analytics or AWS Certified Solutions Architect are an advantage. Strong communication and stakeholder management skills, with the ability to work across technical and non-technical teams.
Senior Data Engineer
to design, build and operate enterprise-grade data platforms supporting analytics, data science and digital products. The role will contribute to data architecture, engineering standards and technical decision-making in a complex enterprise environment.
Responsibilities Design and implement scalable ETL/ELT data pipelines using AWS services including Glue, Step Functions, Lambda, and S3. Build and optimise data lakehouse solutions using Apache Iceberg or S3 Tables, including schema/partition evolution and ACID transactions. Develop automated data quality validation and monitoring frameworks to ensure data accuracy, completeness, and consistency. Develop production-quality code and deploy solutions using CI/CD and Infrastructure-as-Code tools such as Terraform or CloudFormation. Optimise solutions for performance, scalability, cost, and reliability. Collaborate with cross-functional teams, communicate technical solutions to non-technical stakeholders, and prepare documentation for handover to the Day 2 operations team.
Requirements Degree in Computer Science, Data Engineering, Information Systems, or a related discipline. 3–5 years of experience in data engineering, ETL/ELT development, or data platform roles. Strong hands-on experience with AWS and modern data engineering practices. Proficiency in Apache Iceberg or similar open table formats and data lakehouse architectures. Experience with data quality, governance, CI/CD, and Infrastructure-as-Code. Experience in a Government Commercial Cloud (GCC) environment is strongly preferred. AWS certifications such as AWS Certified Data Analytics or AWS Certified Solutions Architect are an advantage. Strong communication and stakeholder management skills, with the ability to work across technical and non-technical teams.