Mid-to-Senior Databricks Data Engineer

Role Overview

Join a data-driven enterprise as a mid-to-senior Databricks Data Engineer, working on high-visibility projects and shaping the future data landscape. The role involves designing and building robust data pipelines, implementing data governance, and managing complex workflows.

What You Will Do

Designing and building high-performance batch and streaming data pipelines, implementing the Medallion architecture on Delta Lake, and managing and automating complex workflows using Databricks Lakeflow or adjacent orchestration tools.

Why It Might Be a Fit

The role offers impact and ownership, a tech-first culture, growth opportunities, and a flexible work-life balance. The ideal candidate is a proactive problem-solver with a strong grasp of engineering best practices and the ability to explain complex technical concepts to non-technical stakeholders.

Requirements

• 3-5+ years of dedicated Data Engineering experience
• Deep, hands-on expertise in the Databricks platform
• Advanced proficiency in Python (PySpark) and SQL
• Strong experience working within a major public cloud ecosystem (Azure Databricks and ADLS Gen2 is highly preferred, but AWS is also welcomed)
• A strong grasp of Git, CI/CD, testing frameworks, and modern software engineering principles applied to data
• The ability to explain complex technical concepts to non-technical stakeholders clearly and concisely

Benefits

• Impact & Ownership: Work on high-visibility projects where your technical decisions will directly shape the future data landscape of a major organisation.
• Tech-First Culture: Join a business that views data as its core asset, meaning you will always have access to modern tools and training.
• Growth: A generous professional development budget tailored to getting you certified in advanced cloud and Databricks competencies.
• Flexibility: A genuine commitment to work-life balance, offering a mature hybrid working model (3 days in their modern Melbourne CBD office, 2 days remote).

Tagged as: Data Analysis, Python, SQL