This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer based in Australia.
This role offers the opportunity to help build, maintain, and modernize a growing data platform in a cloud-first environment. You will design reliable data pipelines and scalable data solutions that enable teams to access and use high-quality information effectively. The role combines modern AWS infrastructure with opportunities to improve and transition legacy data processes. You will work across batch and real-time data workflows, APIs, integrations, and data warehouse solutions. Collaboration with analytics teams and other stakeholders will be central to understanding requirements and delivering practical solutions. This is a hands-on opportunity to improve data reliability, performance, security, and quality while contributing to the evolution of the broader data architecture.
Accountabilities
- Design, develop, and maintain scalable and reliable data pipelines and Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes.
- Develop, maintain, and optimize data warehouse solutions and data models.
- Build and maintain data infrastructure primarily on Amazon Web Services (AWS), while supporting relevant legacy systems.
- Develop APIs and data integrations to enable effective data exchange across systems.
- Contribute to real-time data pipelines and processing using Apache Kafka.
- Automate and optimize data processes, workflows, and operational tasks.
- Monitor, troubleshoot, and continuously improve the reliability, performance, security, and data quality of pipelines and infrastructure.
- Work closely with analytics teams and other stakeholders to understand data requirements and deliver effective technical solutions.
- Maintain accurate and up-to-date documentation covering pipelines, infrastructure, workflows, and operational processes.
- Contribute to the modernization of legacy data processes, infrastructure, and overall data architecture.
Requirements
- 2+ years of professional experience in data engineering.
- Strong SQL and Python programming skills.
- Hands-on experience with AWS services, particularly Amazon S3, Amazon Redshift, AWS Glue, and AWS Lambda.
- Practical experience with Apache Airflow for data workflow orchestration.
- Strong understanding of data warehousing principles and data modeling.
- Experience designing, developing, and maintaining production-grade data pipelines, with a strong focus on reliability, monitoring, and data quality.
- Solid understanding of both relational and non-relational databases.
- Familiarity with Git and Continuous Integration/Continuous Deployment (CI/CD) practices, preferably using GitLab.
- Experience developing APIs and building data integrations.
- Strong written and verbal communication skills.
- Upper-intermediate English proficiency or higher.
- Experience with Kafka and real-time data processing is a plus.
- Experience with Microsoft SQL Server and SQL Server Integration Services (SSIS) is a plus.
Benefits
- Full-time position.
- Opportunity to work within an Analytics-focused environment.
- Remote working arrangement.
- Opportunity to contribute to modern cloud-based data infrastructure.
- Hands-on exposure to AWS, Airflow, Kafka, data warehousing, and data modernization initiatives.
- Opportunity to contribute to the improvement of data reliability, quality, performance, and architecture.
- Collaborative work with analytics teams and cross-functional stakeholders.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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