Lead Data Engineer

Whizdom; Canberra; Hybrid; AUD 150,000 - 190,000; Full time

Job summary

Whizdom is seeking a Lead Data Engineer to join the Enterprise Analytics team in Canberra. You will drive design, development and testing of data movement, transformation and visualisation pipelines across cloud platforms.

The role requires at least 5 years of data engineering experience, strong leadership, and the ability to work in an Agile, cross-disciplinary environment. Hybrid work arrangements in Canberra are available.

Qualifications

• Demonstrated ETL/ELT experience with large data movement.
• Experience delivering data products and analytics visualisations.
• Strong stakeholder collaboration in an Agile environment.

Responsibilities

• Lead design, development, and testing of data movement and transformation.
• Develop data ingest and transformation solutions for analytics use cases.
• Collaborate with multi-disciplinary teams to meet priorities.
• Provide guidance and engage in quality reviews with delivery teams.
• Design and implement automated ingestion frameworks.

Skills

ETL/ELT development

Leadership and collaboration

Agile development

Tools

Azure Databricks

Power BI

Azure Data Factory

SQL Server

Data Lake Storage

Job description

Seeking a Lead Data Engineer with at least 5 years’ experience working as a data engineer.

Job details

The Department 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. 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.

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.

The successful candidate will require experience with the following techniques and technologies

• 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.

Essential criteria

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

Desirable criteria

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

Contract

12 Month Contract with 1 x 12 months extension option

Security Required

NV1 Security Clearance required

Location

Canberra, Hybrid- Candidates may be permitted to work remotely up to 2-days per week.

Closing date

Monday19 October 2026