Lead Data Engineer (Multiple Roles)
Australian citizenship required. No PR or Work Visa holders. Must be able to obtain Baseline security clearance.
Those with an active clearance and based in Canberra highly preferred.
What to submit?
* A tailored resume in docx format
* Individual responses to each criterion (max 3000 characters each)
RFQ Details
* RFQ ID: LH-04270
* Closing Date: Wednesday, 20 August 2025 11:59pm (Canberra time)
* Estimated Start Date: Wednesday, 01 October 2025
* Initial Contract Duration: 12 months
* Extension Term: 12 months
* Number of Extensions: 2
* Experience Level: Lead EL1 equivalent
* Security Clearance: Must be able to obtain Baseline
Client Details
* Agency: Department of Agriculture, Fisheries and Forestry
* Location of Work: ACT
* Working Arrangements: Hybrid Staff expected to attend Canberra office 3 days per week. Participation in Agile ceremonies and key events in person is required.
* Maximum Hours: 40 hours per week
Job Details
The Department of Agriculture, Fisheries and Forestry (DAFF) is seeking Lead Data Engineers to join the Enterprise Analytics section. The successful candidates will work across data and analytics platforms to develop ETL/ELT processes, data products, and complex visualisations using modern cloud technology (Azure).
Key Duties And Responsibilities
* Design, build and test ETL and ELT processes on Azure data platforms
* Design and implement data storage solutions for evolving needs
* Apply expert knowledge to uplift maturity and governance practices
* Participate as an agile team member - responsive, collaborative, and flexible
* Develop and maintain data frameworks and strategies
* Mentor junior engineers and perform quality reviews
* Act as technical escalation point and support the delivery of outcomes
* Build stakeholder relationships and communicate effectively
* Support project teams in alignment with organisational goals
Technical Skills
* Microsoft Azure Stack:
o Data Integration: Azure Data Factory, SSIS, Databricks
o Data Storage: SQL Server, Data Lake Storage
o Analytics: Azure Databricks, Azure Machine Learning, ArcGIS Enterprise
* Development Tools: DevOps, Visual Studio, VS Code
* Data Technologies: Oracle, Ingres, Azure, SQL Server (sourcing, collecting, ingesting, storing)
* Data Preparation: Parquet and/or Delta formats tailored for analytics
Selection Criteria
Individual responses required for each criterion (max 3000 characters each)
Essential Criteria
* Demonstrated experience developing ETL/ELT processes for complex and/or large data movement, transformation and/or visualisations, particularly in a cloud environment. (50%)
* Experience preparing data optimised for query performance in cloud computed engines (e.g. Spark, Graph Databases, Azure SQL). (25%)
* Experience working with Engineering, Storage and Analytics services in cloud infrastructure. (25%)
Desirable Criteria
* Experience working with Azure Data Factory and Databricks
* Experience/Knowledge of working with Data Lake and Lakehouses
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