Lead Data Engineer
Australian citizenship required.
Must be able to obtain Negative Vetting Level 1 security clearance.
Location: Canberra (Hybrid).
What to Submit
A tailored resume in docx format
Individual responses to each criterion (maximum **** characters per criterion)
RFQ Details
RFQ ID:
LH-*****
Agency:
Department of Agriculture, Fisheries and Forestry
Closing Date:
Tuesday, 20 October *********:59pm (Canberra time)
Estimated Start Date:
Monday, 09 November ****
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 solid 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
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. Distributed computing engines (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.
#J-*****-Ljbffr

📌 Lead Data Engineer – Azure | Nv1 | Canberra
🏢 Pinaka Technology Solutions
📍 Canberra