St Vincent's Health Australia
Data Engineer
Builds and maintains ETL/ELT data pipelines feeding St Vincent's Health Australia's enterprise data platform, supporting reporting, analytics, ML and generative AI. Works with Microsoft Azure stack (Azure Data Factory, Azure SQL, Databricks/Microsoft Fabric, Power BI) in a permanent full-time Melbourne role with hybrid working.
- Compensation
- Not disclosed
- Location
- Melbourne VIC
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Full time
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Minimum 5 years experience in data engineering, modeling, architecture, and warehousing
- Tertiary qualification in Information Technology, Health Informatics, or related discipline
- Experience designing and building enterprise ETL/ELT solutions with Microsoft Azure and Azure Data Factory
- Experience with modern lakehouse architectures such as Databricks or Microsoft Fabric
- Advanced SQL capabilities
- Strong programming proficiency in Python or Scala
- Deep understanding of data warehouse architecture and dimensional modeling
- Strong data profiling, cleansing, and systems analysis skills
- Experience developing Power BI dashboards and tabular models (Azure Analysis Services, SSAS)
- Software engineering best practices: Git, CI/CD, automated testing
- Excellent communication, problem-solving, and stakeholder engagement skills
- Understanding of healthcare data privacy standards
- Flexibility to support operational requirements and occasional on-site travel
Nice to have
- Exposure to Infrastructure as Code and containerization
- Experience or practical exposure to Generative AI (Azure OpenAI, RAG, prompt engineering), vector databases, and predictive analytics
Full description
About the role
St Vincent's Health Australia has committed, through Strategy 2030, to connecting care across its public hospitals, private hospitals, aged care and virtual care services, with half of all care delivered virtually or in people's homes by 2030.
As a Data Engineer, you will manage and develop the data pipelines that feed St Vincent's Health Australia's enterprise data platform and underpin reporting, analytics, machine learning and emerging Generative AI solutions.
You will:
- Build and maintain trusted data pipelines that support reporting, analytics, machine learning and AI use cases across the organisation.
- Work with modern Microsoft data technologies, including Azure Data Factory, Azure SQL, Power BI, Databricks or Microsoft Fabric.
- Shape data models, integration patterns and engineering standards for the enterprise data platform.
- Work closely with business, technical and governance stakeholders to ensure data is secure, governed, accurate and fit for purpose.
Key responsibilities of the role
- Design, build, and maintain end-to-end ETL/ELT pipelines to profile, cleanse, and integrate multi-source data across modern platforms like Azure Data Factory, Azure SQL, Databricks or Microsoft Fabric.
- Design enterprise data architectures and dimensional models (facts, dimensions, hierarchies) while evaluating risks and impacts.
- Monitor and maintain data warehouse environments to ensure high reliability, optimal performance, and cost efficiency.
- Apply software engineering best practices to data solutions, including Git version control, CI/CD automation, testing, and configuration management.
- Implement robust security, access controls, data lineage, and automated quality checks within established governance frameworks.
- Build, enhance, and integrate master-data capabilities across enterprise reporting and analytics platforms.
- Create and maintain tabular data models using Power BI, Azure Analysis Services, and SSAS.
- Provide operational troubleshooting for production services and participate in scheduled after-hours support when required.
- Develop and maintain technical documentation, system configuration records, support guides, and training materials.
- Collaborate with internal and external stakeholders to communicate system updates, resolve issues, and ensure data products meet business requirements.
Things that work for us
- Minimum five years of experience across data engineering, modeling, architecture, and warehousing, supported by a tertiary qualification in Information Technology, Health Informatics, or a related discipline.
- Proven experience designing and building enterprise ETL/ELT solutions using Microsoft Azure, Azure Data Factory, and modern lakehouse architectures such as Databricks or Microsoft Fabric.