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
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