Data Engineer - AWS Data Lakehouse (Public Sector)
At a glance
Mid-level Data Engineering role at Xtremax Pte. Ltd. Singapore · contract.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build AWS pipelines that move data through ETL or ELT workflows using Glue, Step Functions, Lambda and S3
- Create lakehouse structures with Iceberg or S3 Tables, including support for changing schemas, partitions and transactions
- Improve pipeline and lakehouse performance while balancing cost, scale and reliability
- Set up automated checks and monitoring for data accuracy, completeness and consistency across the platform
- Ship production code, maintain CI/CD and infrastructure-as-code, and document solutions for operations handover
What you bring
- A degree in computer science, data engineering, information systems or a related discipline
- At least eight years in data engineering, ETL/ELT development or data platform work
- Hands-on AWS delivery experience, including Glue, Step Functions, Lambda and S3
- Practical experience with Iceberg or a comparable open table format, plus lakehouse architecture knowledge
Who this fits
This role suits a senior, hands-on data engineer who can build and deploy AWS lakehouse solutions and explain technical choices to non-technical stakeholders. It is an onsite contract role in Singapore.
From the employer
At Xtremax, we are looking for a Data Engineer to design and build a scalable data lakehouse platform on AWS. You will work across data architecture, pipeline engineering, data quality, governance, and cloud deployment to deliver production-ready solutions that form the foundation of a modern data platform.
This role is suited to an experienced data engineer who enjoys solving complex data engineering challenges at scale. You will work hands-on with AWS services such as Glue, Step Functions, Lambda, and S3, while applying modern lakehouse technologies including Apache Iceberg or S3 Tables. You will also contribute to automated data quality frameworks, CI/CD, infrastructure as code, and production deployments.
You will collaborate with cross-functional teams to translate technical designs into reliable solutions, communicate architecture clearly to non-technical stakeholders, and produce documentation that enables a smooth transition to Day 2 operations.
Responsibilities
- Design and implement scalable ETL/ELT pipelines using AWS Glue, Step Functions, Lambda, S3, and related AWS services
- Architect and build data lakehouse solutions using Apache Iceberg or S3 Tables, including schema evolution, partition evolution, and ACID transactions
- Optimise data pipelines and lakehouse workloads for performance, cost efficiency, scalability, and reliability
- Design and implement automated data quality validation frameworks covering data accuracy, completeness, consistency, and related quality metrics
- Establish data quality monitoring and governance practices across the data platform
- Develop production-quality code and deploy reliable data solutions on AWS
- Build and maintain CI/CD pipelines and infrastructure-as-code using tools such as Terraform or CloudFormation
- Apply DevOps practices to make cloud deployments repeatable, consistent, and auditable
- Work closely with cross-functional teams and communicate technical architecture and design decisions to non-technical stakeholders
- Produce clear technical documentation and support the handover of solutions to the Day 2 operations team
Requirements
- Degree in Computer Science, Data Engineering, Information Systems, or a related discipline
- At least 8 years of experience in data engineering, ETL/ELT development, or data platform roles
- Strong hands-on experience designing and building data solutions on AWS
- Strong experience with AWS services such as Glue, Step Functions, Lambda, and S3
- Hands-on experience with Apache Iceberg or similar open table formats
- Strong understanding of modern data lakehouse architecture and concepts
- Experience designing scalable and reliable data pipelines
- Strong understanding of data quality, validation, monitoring, and governance practices
- Experience writing production-quality code and deploying applications on cloud infrastructure
- Experience with CI/CD and infrastructure-as-code practices
- Strong understanding of Apache Iceberg capabilities and/or S3 table optimisation techniques
- Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders
Preferred
- Experience working in a Government Commercial Cloud (GCC) environment
- AWS Certified Data Analytics certification
- AWS Certified Solutions Architect certification
- Experience with Terraform or CloudFormation
- Experience designing data platforms for large-scale production environments
Benefits
By submitting your resume/CV, you consent and agree to allow the information provided to be used and processed by or on behalf of Xtremax Pte Ltd for purposes related to your registration of interest in current or future employment with us and for the processing of your application for employment.
You also represent to us that you have obtained the consent of your referees when you disclose to us their personal data for the purpose of conducting reference checks.
The personal data held by us relating to your application will be kept strictly confidential and in accordance with the PDPA. You may also refer to our Privacy Policy for more details here:
We regret to inform you that should you not consent to providing the necessary data required for us to process your application, your application will be considered void.
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