Data Engineering Lead

St Vincent's Health Australia

Data Engineering & Innovation Lead at St Vincent's Health Australia guiding AI and data platform transformation. Overseeing integration of real-time data and analytics in healthcare.

Posted 5/29/2026full-timeMelbourne • 🇦🇺 AustraliaSeniorWebsite

Tech Stack

Tools & technologies

AzureCloudETLIoT

About the role

Key responsibilities & impact

Serve as the technical platform owner for our modern Data & AI platform.
Lead the design, implementation and evolution of data engineering solutions that enable real-time data processing, IoT integration, and advanced analytics capabilities across the organisation.
Drive innovation through Generative AI and Machine Learning capabilities, establishing frameworks and pipelines that enable predictive analytics, intelligent automation and data-driven decision making to transform patient care and operational efficiency.
Enable data democratisation by building robust, user-friendly data pipelines and self-service analytics capabilities that empower stakeholders across the organisation to access and leverage data insights independently and securely.
Design and implement cloud-native data architectures including data lakes, lakehouses, streaming platforms and interoperability layers.
Establish data modelling standards, ETL/ELT processes and data quality frameworks that support scalable, reliable data operations.
Build strong relationships with clinical, operational and technical stakeholders to understand data needs, gather requirements and implement process change management.
Act as a trusted advisor on data engineering best practices and innovation opportunities.
Ensure the Mission, Vision, Creed, and Values of SVHA (Compassion, Justice, Integrity, Excellence) are effectively integrated into all areas of responsibility, maintaining ethical data practices and patient-centered technology solutions.

Requirements

What you’ll need

Tertiary qualification Degree in Data Science, Statistics, Computer Science, or a related field
Extensive experience in data engineering, data architecture, and modern cloud-native data platforms (Azure preferred, Fabric, databricks, snowflake desirable)
Proven track record of leading data engineering initiatives and serving as a platform owner for enterprise data solutions
Strong expertise in data modelling, ETL/ELT pipelines, data warehousing, and real-time data processing
Experience with AI/ML platforms, including Generative AI integration and MLOps practices
Demonstrated ability to design and implement self-service analytics and data democratisation initiatives
Deep understanding of data governance, data quality frameworks, and interoperability standards (particularly in healthcare)
Excellent stakeholder management and communication skills, with ability to translate technical concepts for diverse audiences
Experience driving innovation and continuous improvement in complex organisational environments
Data, infrastructure and/or AI certifications by recognised providers (Microsoft, , Databricks, Snowflake etc.)
Knowledge and experience of the health industry and healthcare data standards (HL7, FHIR)
Experience with IoT data platforms and real-time streaming technologies
Track record of leading digital transformation initiatives in large, complex organisations

Benefits

Comp & perks

Competitive salary packaging options
Discounted private health insurance
Employee Assistance Program for staff and their families
Access to the Fitness Passport (FP)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringdata architecturecloud-native data platformsdata modellingETLELTreal-time data processingGenerative AIMLOpsself-service analytics

Soft Skills

stakeholder managementcommunication skillsprocess change managementinnovationcontinuous improvementrelationship buildingtechnical translation

Certifications

Microsoft certificationsDatabricks certificationsSnowflake certifications