Job Description

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.

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This role offers the opportunity to help build, maintain, and modernize a growing data platform in a cloud-first setting. 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.

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Accountabilities

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- Design, develop, and maintain scalable and reliable data pipelines and Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes.
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- Develop, maintain, and optimize data warehouse solutions and data models.
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- Build and maintain data infrastructure primarily on Amazon Web Services (AWS), while supporting relevant legacy systems.
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- Develop APIs and data integrations to enable effective data exchange across systems.
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- Contribute to real-time data pipelines and processing using Apache Kafka.
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- Automate and optimize data processes, workflows, and operational tasks.
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- Monitor, troubleshoot, and continuously improve the reliability, performance, security, and data quality of pipelines and infrastructure.
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- Work closely with analytics teams and other stakeholders to understand data requirements and deliver effective technical solutions.
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- Maintain accurate and up-to-date documentation covering pipelines, infrastructure, workflows, and operational processes.
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- Contribute to the modernization of legacy data processes, infrastructure, and overall data architecture.
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Requirements

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- 2+ years of professional experience in data engineering.
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- Strong SQL and Python programming skills.
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- Hands-on experience with AWS services, particularly Amazon S3, Amazon Redshift, AWS Glue, and AWS Lambda.
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- Practical experience with Apache Airflow for data workflow orchestration.
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- Strong understanding of data warehousing principles and data modeling.
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- Experience designing, developing, and maintaining production-grade data pipelines, with a strong focus on reliability, monitoring, and data quality.
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- Solid understanding of both relational and non-relational databases.
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- Familiarity with Git and Continuous Integration/Continuous Deployment (CI/CD) practices, preferably using GitLab.
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- Experience developing APIs and building data integrations.
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- Strong written and verbal communication skills.
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- Upper-intermediate English proficiency or higher.
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- Experience with Kafka and real-time data processing is a plus.
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- Experience with Microsoft SQL Server and SQL Server Integration Services (SSIS) is a plus.
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Benefits

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- Full-time position.
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- Opportunity to work within an Analytics-focused environment.
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- Remote working arrangement.
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- Opportunity to contribute to up-to-date cloud-based data infrastructure.
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- Hands-on exposure to AWS, Airflow, Kafka, data warehousing, and data modernization initiatives.
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- Opportunity to contribute to the improvement of data reliability, quality, performance, and architecture.
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- Collaborative work with analytics teams and cross-functional stakeholders.
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📌 Data Engineer (New South Wales)
🏢 Jobgether
📍 New South Wales