Data Engineer

Sirius.; Melbourne; Hybrid; AUD 110,000 - 150,000; Full time

Benefits offered by this job

Hybrid work model

Professional development budget

Melbourne CBD office access

Job summary

Sirius. in Melbourne is seeking a mid-to-senior Databricks Data Engineer to shape a modern, enterprise-scale data ecosystem. You will design robust data pipelines, champion Lakehouse architecture on Delta Lake, and drive the transformation of analytics and ML capabilities across the organization.

This role features a genuine Hybrid model (3 days in Melbourne CBD office, 2 days remote) and a strong bias toward design leadership. Applicants must have PR or Australian citizenship.

Qualifications

• 3–5+ years of dedicated Data Engineering experience.
• Deep, hands-on expertise in the Databricks platform and PySpark.
• Strong proficiency in SQL and data modeling for analytics.
• Experience with Delta Lake and data governance practices.

Responsibilities

• Designing and building high-performance batch and streaming data pipelines using PySpark, SQL, and the Databricks ecosystem.
• Championing the Medallion architecture (Bronze, Silver, Gold) on Delta Lake for data quality.
• Implementing robust access controls, data lineage, and Unity Catalog governance.
• Managing and automating workflows with Lakeflow, Airflow, or similar tools.
• Tuning compute resources and establishing CI/CD pipelines for automated deployments.

Skills

Databricks ecosystem

Python (PySpark)

SQL

Delta Lake

CI/CD

Git

Tools

Databricks

PySpark

Delta Lake

Unity Catalog

Lakeflow

Airflow

ADF

Job description

Are you a Databricks champion looking to leave your mark on a modern, enterprise-scale data ecosystem?

I am partnering exclusively with a highly respected, data-driven enterprise based in Melbourne. They are currently undergoing a massive transformation of their data capabilities and are heavily investing in the Databricks Lakehouse architecture to power their next generation of advanced analytics and machine learning initiatives.

Due to continuous growth, they are looking for a mid-to-senior Databricks Data Engineer to join their high-performing data team. This is not a "maintain the status quo" role, you will have a loud voice in design decisions and play a critical part in building robust, scalable data pipelines from the ground up.

Please note: You must hold PR, or be an Australian Citizen for this role.

What You Will Be Doing

As a core member of the data engineering squad, you will sit at the intersection of data science, analytics, and platform engineering. Your day-to-day will involve:

• Designing and Building: Developing high-performance batch and streaming data pipelines utilising PySpark, SQL, and the Databricks ecosystem.
• Lakehouse Architecture: Championing and implementing the Medallion architecture (Bronze, Silver, Gold) on Delta Lake to ensure pristine data quality for downstream consumers.
• Data Governance: Implementing robust access controls, security policies, and data lineage tracking using Databricks Unity Catalog.
• Orchestration: Managing and automating complex workflows using Databricks Lakeflow (Workflows) or adjacent orchestration tools like ADF/Airflow.
• DevOps & Optimization: Tuning cluster compute for performance and cost-efficiency, and setting up rock-solid CI/CD pipelines for automated deployments.
• Stakeholder Engagement: Partnering with cross-functional teams to translate complex business requirements into elegant technical solutions.

Technical Requirements

My client is looking for a proactive problem-solver who takes pride in writing clean, efficient code. You will need:

• Proven Experience: 3-5+ years of dedicated Data Engineering experience with a history of delivering complex data solutions in production environments.
• Technical Mastery: Deep, hands-on expertise in the Databricks platform, alongside advanced proficiency in Python (PySpark) and SQL.
• Cloud Native: Strong experience working within a major public cloud ecosystem (Azure Databricks and ADLS Gen2 is highly preferred, but AWS is also welcomed).
• Engineering Best Practices: A strong grasp of Git, CI/CD, testing frameworks, and modern software engineering principles applied to data.
• Communication Skills: The ability to explain complex technical concepts to non-technical stakeholders clearly and concisely.
• Bonus points: Holding an active Databricks Data Engineer Associate/Professional certification or having hands-on experience with MLflow.

Why Join This Client?

• 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).