Data Engineering Lead

Role Overview

• 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

• 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
• Desirable: 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

Tech Stack

• Azure
• Cloud
• ETL
• IoT

Benefits

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