Data Engineer

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• Full-time, Ongoing position available - 80 hours per fortnight.
• Up to $130,000.00 to $150,000.00 salary per annum + Salary Packaging + Super + Five Weeks Annual Leave.
• Parkville location with flexible working arrangements.

The Peter MacCallum Cancer Centre (Peter Mac) is a Victorian public health service and a world-leading comprehensive cancer centre, dedicated to excellence across all spheres of clinical care, research and education. We are home to the largest cancer research enterprise in Australia and provide treatment to around 40,000 people with cancer each year. Welcoming staff from diverse backgrounds and experiences is integral to fostering innovation and compassion, and delivering the best possible cancer care for our patients.
About the team
The Digital and Connected Health (DCH) team is transforming the way data is managed, accessed and used across Peter Mac. Working closely with clinical, research, technology and analytics stakeholders, the team is implementing a new Data Management and Analytics Platform (DMAP) in Azure Databricks to support secure, scalable and self service access to enterprise data.
About the role
We are seeking an experienced Data Engineer to play a key role in implementing a Data Management and Analytics Platform built on Azure Databricks, enabling secure, scalable and self service access to high quality data. The Data Engineer will work closely with clinical, research, operational, analytics and technology stakeholders to translate enterprise data requirements into reliable, scalable solutions that support advanced analytics, research, innovation and data driven decision making across the organisation. This is an ongoing position within our Digital and Connected Health team, reporting to the Program Lead.
This position offers an exciting opportunity to contribute to a significant digital trasformation initiative while helping shape the future of data driven cancer care and research.
A regular day will see you:

• Designing, building and maintaining scalable data pielines and analytics ready datasets.
• Developing and supporting enterprise scale cloud data platforms using Azure Databricksand modern engineering practices.
• Implementing data governance, security, privacy and quality controls across data asset.
• Building and maintaining CI/CD pipelines, automation frameworks and infrastructure as ode solutions.
• Collaborating with clinical, research, business and technology stakeholders to deliverhigh value data solutions.
• Supporting data architecture, technical design decisions and platform optimisation iniiatives.
• Creating and maintaining technical documentation, operational runbooks and support proedures.

About you
You are a technically strong and collaborative data professional who enjos solving complex problems and enabling organisations to make smarter decisions through data. You bring a proactive approach to stakeholder engagement, continuous improvement and delivering high quality solutions.
You'll bring with you:

• Relevant tertiary qualifications in Computer Science, Information Technology, Data Engineering, Software Engineering or equivalent experience.
• Demonstrated experience designing, building and supporting enterprise scale cloud dataplatforms.
• Strong expertise in data warehousing, ETL/ELT processes, data modelling and enterpriseintegration patterns.
• Hands on experience with SQL, Python and modern data engineering technologies such as park.
• Experience implementing CI/CD pipelines, infrastructure as code and automated deploymet practices.
• Knowledge of data governance, privacy, security, metadata and data quality frameworks.
• Strong stakeholder engagement and communication skills with the ability to work acrosstechnical and non technical teams.

It would be great if you also have:

• Experience working in healthcare, research o academic environments.
• Exposure to healthcare interoperability standards including HL7v2, FHIR, DICOM or OMOP
• Experience with AI, machine learning, advanced analytics or large language model (LLM)enabled data solutions.

We offer a range of benefits designed to support your career, wllbeing and work life balance, including:

• Salary packaging benefits to increase your take home pay.
• Five weeks annual leave.
• Flexible and hybrid working arrangements.
• Access to health and wellbeing initiatives.
• A collaborative, inclusive and purpose driven workplace.
• The opportunity to contribute to world leading cancer research and care.

Inclusion and belonging
At Peter MacCallum Cancer Centre, we celebrate diversity and are committed to creating an inclusive workplace where everyone feels respected, valued and supported. We welcome applications from Aboriginal and Torres Strait Islander peoples, people from culturally and linguistically diverse backgrounds, members of the LGBTQIA+ community, people with disability and people of all ages.
If you're passionate about building modern data platforms that supprt world class clinical care, research and innovation, we'd love to hear from you.
All appointments are made subject to satisfactory background screening requirements relevant to the role. Successful applicants will be expected to comply with Peter Mac policies, procedures and mandatory training requirements.
For a confidential discussion about this role, please contact:
Contact Number:
Position Summary Peter Mac is seeking a Data Engineer to play a leading role in implementation of a new Data Management and Analytics Platform (DMAP), running in Azure Databricks, to enable secure, scalable, self service access to high quality data.
The Data Engineer will work closely with business, clinical, research, analytics, and technology stakeholders to translate enterprise requirements into robust data solutions to accelerate research, innovation, and data driven decision making across the organization.
The role is responsible for:

• Implementing and supporting enterprise scale data platforms and architectures.
• Building robust, automated data engineering solutions.
• Establishing governance, standards, and operational excellence
• Enabling self service analytics at scale.

Influencing stakeholders and leading cross domain data initiatives that support research, clinical, and organizational outcomes.
Health and Allied Services, Managers and Administrative Workers
Classification or Salary Range HS4
Category C: Position within a non clinical setting
Key Relationships Internal

• Digital & Connected Health team
• Digital Innovation team
• Business Intelligence & Analytics team
• Health Service Research team
• Bioinformatics team
• EMR Optimisation team
• Chief Information Officers

External

• Digital platform vendors
• Local Health Services Network
• University partners
• Government agencies and professional bodies
• Collaborating investigators and their support staff
• Government and research funding bodies
• Regulatory bodies
• Consultants

Skills

• Relevant tertiary qualification in Computer Science, Information Technology, Data Engineering, Software Engineering, or equivalent experience.
• 3 - 5 years experience designing, building, and supporting enterprise-scale data platforms, with a focus on cloud-based technologies and Databricks.
• Deep and solid understanding of, and exposure to:
  • Data warehousing principles, ETL/ELT processes and data modelling techniques.
  • Different phases of data project delivery lifecycle.
  • Enterprise integration patterns, API-based architectures, and interoperability concepts.
  • Self service analytics principles.
  • Working with a data team and understanding their challenges.
• Ability to produce quality technical documentation.
• Strong stakeholder engagement skills working effectively across technical and non technical teams.
  • Demonstrated ability to lead technical decision making and influence architecture, tooling, and engineering standards.
  • Understanding of the Australian Privacy Principles and de identification.
• Demonstrated hands on experience:
  • Building and deploying data engineering pipelines into production, including using automation best practices for CI/CD
  • Implementing data governance and security controls eg role based access, data quality checks, auditability, privacy, sensitive data, consent and de identification.
  • With at least one of AWS/Azure/GCP and the respective data services.
  • Integration of data from multiple enterprise systems.
  • Deploying cloud infrastructure as code (IaC) using Terraform or similar.
  • Performance tuning, optimisation, and scalability of data solutions.
  • Environment management across development, test, staging, and production.
• Proficiency in common:
  • data languages eg SQL, Python.
  • data engineering tools - eg Spark, Kubernetes.
• data governance tools - eg data catalog, metadata.
• Experience working within healthcare, research, or academic environments.
• Experience integrating data from Electronic Medical Record (EMR) systems such as Epic.
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