Data Engineering Specialist (Bris, Syd, Mel)

**About us
**At CareSuper, we believe we're Super Together. As a profit-to-member super fund with over 600,000 members and $60 billion in assets, we're passionate about helping our members retire with confidence. We're growing fast and looking for our next superhero to join us on this exciting journey.

**About the role
**As our new Data Engineering Specialist, you'll be part of our Technology Delivery team. Reporting to the Manager Data Platform, you will be responsible for the design, development and optimisation of our enterprise data platform built on Azure Databricks. You will deliver scalable, cloud-native data engineering solutions in line with our Data Strategy and roadmap, enabling analytics, reporting and advanced insights across the organisation.

A day in the life may look like;

• Providing technical and strategic advice to senior management, staff and stakeholders on Care Super's cloud data platform, data pipelines and analytics enablement.
• Designing, building and optimising data ingestion, transformation and orchestration pipelines using Azure Databricks and associated Azure services.
• Troubleshooting and performance-tuning data engineering workloads, notebooks, jobs and supporting services to ensure reliability and scalability.
• Producing and reviewing technical documentation, solution designs and data models, and analysing business data sources to support analytical and operational use cases.
• Providing guidance and support in the use and development of modern analytics and data engineering tools, enabling self-service analytics where appropriate.
• Completing escalated Level 3 data platform requests and supporting the Insights and Analytics team to resolve complex data issues and queries.

**What we're looking for
**Our ideal candidate will bring strong experience designing and delivering cloud-based data engineering solutions, with a focus on Azure and Databricks.

You'll also bring the following skills:

• Strong SQL and data modelling skills across relational and analytical data stores
• Data ingestion, transformation and orchestration using Azure Databricks (Spark, SQL, Python/Scala)
• Experience with Delta Lake, medallion architecture and modern data platform design patterns
• Integration with Azure services such as Azure Data Lake Storage, Azure Data Factory, Azure Synapse and Power BI
• Knowledge of Agile development methodologies and best practices
• CI/CD practices for data platforms (e.g. Azure DevOps, Git-based workflows)
• Experience supporting analytics, dashboards and KPIs using Databricks or Power BI
• Strong documentation, stakeholder engagement and problem-solving skills