Our client is seeking an experienced Principal Data Engineer to play a key leadership role within a high-performing Data & Analytics team. This is a hands-on senior individual contributor position where you'll help shape the organisation's data platform architecture, drive engineering standards, and influence the technical roadmap.
You'll act as the technical authority across the data lakehouse environment, ensuring high standards of data quality, performance, and reliability, while mentoring engineers and working closely with business stakeholders.
This is initially a 6 month contract, but highly likely to have additional extensions for the right candidate who can drive the implementation and strategy for the client's Data & Analytics solution. The role will be based in the Western Suburbs of Melbourne and an hybrid engagement (3 dpw in the office) is negotiable.
Please note, to apply applicants must have the following:
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The requisite skills and experience defined below,
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At least Australian Permanent Residence working rights,
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At least 8+ years' experience as a Senior Data Engineer, with at least 4 years working in Australia.
Key Responsibilities:
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Design and build scalable data pipelines using Azure Databricks, Delta Live Tables, and Azure Data Factory.
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Architect and evolve medallion (bronze–silver–gold) data layers.
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Govern and extend Unity Catalog (ownership, lineage, access, schema design).
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Lead platform reliability, including SLA monitoring, optimisation, and cost governance.
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Data Quality & Standards.
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Define and enforce engineering standards (naming, testing, CI/CD, documentation).
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Implement and uplift data quality frameworks and observability.
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Drive continuous improvement across ingestion and transformation layers.
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Stakeholder & Team Impact.
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Mentor and guide data engineers; conduct code reviews and uplift capability.
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Translate business requirements into scalable technical solutions.
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Represent Data & Analytics in architecture forums and vendor interactions.
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Support onboarding and integration of external data partners.
Skills & Experience:
Essential -
- 8+ years' experience in data engineering within complex production environments.
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Proven delivery of Data Lakehouse architectures (Delta Lake / Databricks preferred).
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Strong expertise in SQL, Python, and PySpark.
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Hands-on experience with Azure services (ADF, Event Hubs, ADLS Gen2, Synapse).
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Solid data modelling experience.
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Experience working in regulated or critical infrastructure environments.
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Azure Databricks (Unity Catalog, Delta Live Tables, Workflows, MLflow).
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Integration with Microsoft Fabric / Power BI semantic models.
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CI/CD for data pipelines (Azure DevOps, Git workflows).
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Infrastructure-as-code and environment management.
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Data quality and observability tooling (e.g. Great Expectations, Monte Carlo).
Desirable -
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API or MCP server development.
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Experience in aviation, transport, or critical infrastructure.
- Exposure to real-time operational or passenger data.
- Knowledge of AI governance or LLM integration.
- Relevant certifications (Azure Data Engineer, Databricks).
Notes:
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Only shortlisted candidates will be contacted.
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Your daily rate will depend on skills and experience.
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Start date is ASAP.
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Hybrid working engagement negotiable, but from Melbourne, VIC only.
