Data Engineering & Innovation Lead

External

Svha · Vic - Melbourne, Cbd & Inner Suburbs

Full-timeOn-siteToday

AzureData WarehousingETLGenerative AIIoTMachine Learning

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About the role

St Vincent's Health Australia (SVHA) is launching its future as a "Connected, Intelligent Healthcare organisation" to unify data, AI and intelligence across our national footprint. As the Data Engineering & Innovation Lead, you will be the platform owner for our modern data and AI platform, guiding St Vincent's through an exciting transformation to cloud & AI-native data capabilities. This is a unique opportunity to architect and lead the engineering function as we embark on our journey toward real-time IoT data integration, Generative AI and Machine Learning, self-service analytics, and data democratisation across our healthcare ecosystem. You and your team will be responsible for bring structured and unstructured data from multiple sources at many speeds, transforming it into meaningful inputs for advanced analytics and AI. You will also be leading the establishing and growth of cutting edge AI capabilities as St Vincent's navigates its journey to increasingly embedding AI into the services it provides to its patients and residents. Working closely with diverse stakeholders across clinical, operational and corporate functions, you'll build strong partnerships and implement process improvements that unlock the power of data to enhance patient care and operational excellence. This role is part of a broader Data Analytics Community across SVHA, and all activities must align with SVHA's Data Governance & Analytics Strategy and Standards, ensuring we build a sustainable, scalable platform for the future. What you will be doing.

Responsibilities

As Data Engineering & Innovation Lead, you will be expected to:

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.

What You'll Bring.

Essential Experience & Skills:

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 d

Data Engineering & Innovation Lead

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