Data Engineer: Databricks & Modern Data Pipelines

Bupa; Melbourne; In loco; AUD 110.000 - 160.000; Tempo pieno

Descrizione del lavoro

Bupa in Australia is hiring a Data Engineer to design, build and maintain scalable data pipelines and datasets aligned to target-state architectures. You will work across operational data stores, data warehouses and the Databricks platform to deliver reliable, decision-ready data assets.

You'll contribute to data platform modernization, migrate legacy data assets (e.g., SAS datamarts) to cloud-based Databricks, and ensure consistency of business logic across environments while upholding

Competenze

• Tertiary qualification in Computer Science, Information Systems, Data & Analytics, Engineering, or related field.
• At least 2 years of hands-on experience developing, managing and supporting SAS ETL processes.
• At least 1 year of hands-on data engineering with Databricks, migrating SAS pipelines to Databricks is a plus.
• Experience with BI tools such as Power BI and data analytics platforms.

Mansioni

• Design, build and maintain scalable data pipelines and datasets aligned to target-state architectures and standards.
• Develop and optimize data transformations across data stores, warehouses and Databricks.
• Apply ETL/ELT best practices to ensure reliable, reusable and decision-ready data assets.
• Contribute to data platform modernization and migration initiatives.

Conoscenze

Data engineering

ETL/ELT design

Dimensional modelling

Data governance

Formazione

Bachelor's degree in Computer Science / Information Systems / Data & Analytics / Engineering

Strumenti

SAS

Databricks

Power BI

Descrizione del lavoro

Bupa in Australia is hiring a Data Engineer to design, build and maintain scalable data pipelines and datasets aligned to target-state architectures. You will work across operational data stores, data warehouses and the Databricks platform to deliver reliable, decision-ready data assets.

You'll contribute to data platform modernization, migrate legacy data assets (e.g., SAS datamarts) to cloud-based Databricks, and ensure consistency of business logic across environments while upholding