Lead Data Engineer – Azure | NV1 | Canberra

Lead Data Engineer

Australian citizenship required. Must be able to obtain Negative Vetting Level 1 security clearance.
Location: Canberra (Hybrid).

What to Submit

1. A tailored resume in docx format
2. Individual responses to each criterion (maximum 3000 characters per criterion)

RFQ Details

• RFQ ID: LH-08070
• Agency: Department of Agriculture, Fisheries and Forestry
• Closing Date: Tuesday, 20 October 2026 – 11:59pm (Canberra time)
• Estimated Start Date: Monday, 09 November 2026
• 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 Negative Vetting Level 1 security clearance
• Location of Work: ACT
• Working Arrangements: Hybrid. Most of the section is located at Agriculture House in Canberra CBD. The standard expectation is for staff to attend the office three (3) working days each week. The section is supportive of flexible arrangements and consideration will be made to accommodate individual and collaboration needs. In-person attendance at important Agile ceremonies (currently held quarterly) and other important team / section events is a requirement.
• Maximum Hours: 40 hours per week

Job Details

The Department of Agriculture, Fisheries and Forestry (DAFF) is looking for a Data Engineer to join its Enterprise Analytics and Technology Services (EATS) section to work across its data and analytics platforms. We are seeking candidates with strong experience in developing Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes, and /or the development of data products and complex data visualisations.
The role will be responsible for design, development and testing activities across several data movement, data transformation, and data visualisation processes within DAFF. The data movement and transformation processes focus on the preparation of data for use in decision making processes across the department, utilising modern cloud technology (Azure & Databricks) to enable operational analytics use cases.
To be successful in the role, you must have a strong work ethic including taking ownership, providing leadership, having a high level of productivity, and working with a multi-disciplinary team in an Agile development environment. You must have suitable qualifications or training in data engineering techniques and at least 5 years’ experience working as a data engineer.
Candidates must hold a valid Negative Vetting Level 1 security clearance or be willing and eligible to obtain one. Commencement within the section is contingent on the candidate obtaining a Baseline clearance. Please provide your CSID on your resume/CV (if known).

Key Duties and Responsibilities

• Be responsive, flexible, and work collaboratively as part of an agile team.
• Strong relationship building, and negotiation skills.
• Strong written and oral communication skills.
• Creating and maintaining automated ingest and transformation patterns and frameworks. Designing, building and maintaining data ingest and transformation solutions to meet current and emerging needs.
• Assisting project teams achieve objectives that align with departmental, divisional, and program priorities.
• Supporting data engineers in delivery teams, through regular quality reviews and constructive feedback on utilising data assets to produce quality data products.
• Azure hosted services including:
  • Data Integration - Data Factory, SQL Server Integration Services and/or Databricks
  • Data Store - SQL Server and/or Data Lake Storage
  • Analytics - Azure Databricks, Azure Machine Learning, ArcGIS Enterprise
• Development tools – DevOps, Visual Studio
• Data technology solutions – sourcing (Oracle, Ingres, Azure, SQL Server), automated ingestion
• Data Preparation
  • Transformation of data into formats tailored for advanced analytics and AI use cases – Parquet and/or Delta
• Data Visualisation
  • Analyse and interpret complex data sets, and to identify trends and patterns.
  • Design principles to create appropriate visualisations for target audience.
  • Visualisation tools - Power BI.

Technical Skills

See above.

Selection Criteria

Essential criteria

1. Demonstrated experience developing ETL/ELT processes for complex and/or large data movement, transformation and/or visualisations, particularly in a cloud environment. 50%
2. Experience preparing data optimised for query performance in cloud computed engines. E.g. Distributed computing engines (Spark) Graph Databases Azure
   SQL 25%
3. Experience working with Engineering, Storage and Analytics services in cloud infrastructure. 25%

Desirable criteria

1. Experience working with Azure Data Factory and Databricks.
2. Experience/Knowledge of working with Data Lake and Lakehouses.