Principal Data Engineer

Evaluate emerging technologies and identify opportunities to innovate across data, cloud, and AI ecosystems.

Act as a senior technical advisor to engineering leaders, architects, and business stakeholders.

Establish engineering standards, frameworks, and best practices that scale across the organisation.

Mentor and coach engineers, fostering a culture of continuous learning, collaboration, and technical excellence.

Solution Design & Delivery

Lead the design and implementation of scalable lakehouse architectures and enterprise-grade data platforms using Databricks.

Develop reusable frameworks, accelerators, libraries, and reference implementations to improve delivery velocity.

Partner with Engineering Leads and Data Architects to solve complex business challenges through data-driven solutions.

Guide teams on:

Data modelling and architecture patterns

Data quality frameworks

Pipeline orchestration

Metadata management

AI/ML lifecycle management

Facilitate technical workshops, platform onboarding sessions, and capability uplift across multiple delivery squads.

Communicate complex technical concepts effectively to both technical and non-technical audiences.

Platform Excellence & Support

Contribute to and help lead a Data Platform Centre of Excellence (CoE).

Provide hands-on technical expertise across multiple programs and initiatives.

Support and coordinate engineering delivery across globally distributed and offshore teams.

Promote consistency, reliability, maintainability, and scalability across all platform capabilities.

Innovation & Continuous Improvement

Champion modern DataOps and MLOps practices, including:

CI/CD for data and machine learning

Automated testing

Data lineage

Platform observability and monitoring

Drive continuous improvement initiatives to reduce technical debt and improve engineering productivity.

Develop tools and automation capabilities that streamline the development and deployment of data products.

Influence the adoption of modern cloud-native and AI-enabled engineering practices.

About You

Essential Experience & Skills

Databricks & Data Engineering

Expert-level experience with Databricks, including:

Delta Lake

Unity Catalog

MLflow

Databricks SQL

Advanced expertise in PySpark, Spark SQL, and distributed data processing.

Strong experience designing and implementing modern lakehouse architectures.

Deep knowledge of data modelling methodologies, including dimensional modelling, Data Vault, and feature store design.

Experience with orchestration tools such as Airflow, Databricks Workflows, or Azure Data Factory.

AI/ML Platform Engineering

Proven experience enabling machine learning workloads at enterprise scale.

Experience building feature pipelines, model training pipelines, and model deployment frameworks.

Strong understanding of MLOps practices, including:

Model monitoring

Automated retraining

CI/CD for ML

Model governance

Experience partnering with Data Scientists to productionise machine learning models.

DataOps & Cloud Engineering

Strong experience with CI/CD tooling such as GitHub Actions, Azure DevOps, or Jenkins.

Expertise in Infrastructure as Code (Terraform, ARM/Bicep, or CloudFormation).

Strong understanding of data governance, metadata management, security, and compliance controls.

General Engineering

Advanced programming skills in Python and SQL.

Experience working with REST APIs, event streaming technologies (Kafka, Kinesis), and microservices architectures.

Highly Regarded

Experience leading engineering teams across multiple regions and geographies.

Experience with real-time analytics and streaming AI/ML workloads.

Exposure to advanced optimisation techniques and modern AI engineering practices.

Experience with BI and analytics tools such as Power BI or Tableau.

Experience with Azure services including ADLS, Synapse, Event Hub, and Key Vault.

Experience with data quality frameworks.

Databricks and/or AWS cloud certifications.

Experience Required

10+ years' experience in Data Engineering, Software Engineering, or a related field.

5+ years working with Databricks or large-scale Spark platforms.

5+ years designing and delivering cloud-native data solutions.

Demonstrated experience defining technical strategy and influencing enterprise architecture decisions.

Imagine working with us

We understand that work means different things to everyone... We know happy, healthy people make great teams, and great teams put more heart into each customer and patient interaction. And that ’ s why we ’ re reinventing work.

Imagine a workplace that helps you and your family thrive. Where connection, personal development and health and wellbeing are front of mind. To learn more about our benefits go to https://careers.medibank.com.au/culture/rewards-benefits/

For you, work should help you Live Better. It should bring you fulfillment and joy. And with Medibank, it could.

Inclusion and Accessibility

We believe in everyone's potential and strive to make Medibank inclusive for all because different perspectives make us better. We encourage applications from everyone, including Aboriginal and Torres Strait Islander peoples, neurodivergent candidates, LGBTQIA+ community including transgender and gender diverse candidates and candidates with a disability.

If you need adjustments or alternative formats at any stage of the recruitment or employment journey, we’re here to help. You can let us know directly in the application form, or if you’d prefer to discuss before applying, please reach out to us careers@medibank.com.au or (03) 8622 5666. Learn more about our commitments and employee stories at https://careers.medibank.com.au/diversity-inclusion /(please copy and paste the URL onto your browser)

Medibank proudly recognised as Best Enterprise Organisation, 2026 AFR BOSS Best Places to Work

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