Senior Data Engineer
Summary
Senior Data Engineer in Melbourne designing and supporting enterprise-scale data platforms: building scalable batch and real-time pipelines, ETL/ELT workflows, and data lake/warehouse solutions on AWS or Azure, plus monitoring reliability and fixing production data issues. An Australian Baseline Clearance is required.
Join a high-performing data team delivering enterprise-scale data solutions within a complex and evolving technology environment. This role offers the opportunity to work across modern cloud-based data platforms, data lakes, data warehouses, analytics environments, and large-scale data integration initiatives.
About the Role
We are seeking experienced Senior Data Engineers to design, build, support, and enhance enterprise data platforms. You will play a key role in developing scalable data solutions, optimising data pipelines, and supporting critical business intelligence and analytics capabilities.
Working within a collaborative and agile team, you will contribute to the delivery of modern data architectures that support both operational and strategic decision-making.
Key Responsibilities
- Design, develop and maintain scalable data pipelines and data integration solutions.
- Support and enhance enterprise Data Lake and Data Warehouse platforms.
- Build and optimise batch and real-time data processing solutions.
- Develop ETL/ELT frameworks and associated data workflows.
- Implement and maintain CI/CD practices for data engineering solutions.
- Monitor platform performance, reliability and data quality.
- Investigate and resolve data-related incidents and production issues.
- Collaborate with architects, analysts, developers and business stakeholders.
- Contribute to the continuous improvement of data engineering standards and practices.
- Produce technical documentation and support knowledge-sharing initiatives.
Required Skills & Experience
- Baseline Clearance
- Demonstrated experience as a Data Engineer within complex enterprise environments.
- Strong experience working with Data Lakes, Data Warehouses and analytics platforms.
- Experience developing and supporting ETL/ELT solutions.
- Hands‑on experience with cloud‑based data platforms (AWS and/or Azure).
- Strong SQL and data engineering capabilities.
- Experience building scalable data pipelines and integration solutions.
- Knowledge of CI/CD methodologies and DevOps practices.
- Experience supporting production data platforms and resolving operational issues.