Databricks Data Engineer

Salary: $800pd

We’re seeking a skilled Data Engineer with strong hands-on experience across Databricks, data modelling and Power BI to join a Melbourne-based team. This is an exciting opportunity for someone who enjoys building scalable data solutions, transforming complex datasets into meaningful insights, and enabling better business decision-making through high-quality data.
You’ll work across the data lifecycle, from ingestion and transformation through to data modelling and reporting, collaborating with technical teams and business stakeholders to deliver reliable, fit-for-purpose data solutions.

In this role, you will:

• Design, develop and maintain scalable data pipelines using Databricks, supporting efficient data ingestion, transformation and processing.
• Build and optimise data solutions using PySpark, Spark SQL and SQL.
• Develop and maintain robust data models to support analytics, reporting and business intelligence requirements.
• Work with data engineers, analysts and business stakeholders to translate requirements into effective technical solutions.
• Support the development of reporting and visualisation solutions using Power BI, ensuring data is accurate, accessible and meaningful.
• Improve data quality, performance and reliability across the data platform.
• Apply best practices in data architecture, modelling, transformation and development.
• Troubleshoot data issues and identify opportunities to improve performance, scalability and efficiency.
• Contribute to the ongoing enhancement of data engineering practices and platform capabilities.

To be successful in this role, you will bring:

• Proven experience as a Data Engineer or in a similar data-focused role.
• Strong hands-on experience with Databricks and modern data engineering practices.
• Solid SQL skills and experience working with complex datasets.
• Strong understanding of data modelling principles, including designing efficient models for analytics and reporting.
• Experience developing Power BI reports and dashboards, with an understanding of the underlying data models.
• Experience with PySpark, Spark SQL or similar data transformation technologies.
• A sound understanding of data warehousing, data pipelines and ETL/ELT processes.
• Strong analytical and problem-solving skills, with a focus on data quality and performance.
• Excellent communication skills and the ability to work collaboratively with both technical and non-technical stakeholders.

Why consider this opportunity?

• Work across a modern data technology stack.
• Take ownership of meaningful data engineering and modelling initiatives.