Location:

Canberra CBD, ACT | Hybrid

Engagement:

12-month contract, with two possible 12-month extensions

About INGRITY:

INGRITY is a specialist Data, Digital, Cloud & AI consultancy, helping organisations turn complex data into practical business outcomes.

About the Role:

You’ll lead the design, build and testing of data ingestion, transformation and visualisation solutions across Azure and Databricks, preparing data to support decision-making across the department.

What You’ll Do:

- Design, build, test and maintain data ingestion and transformation solutions that meet current and emerging needs.
- Develop reusable, automated ingestion and transformation patterns and frameworks.
- Prepare data for analytics, visualisation and AI use cases, with a focus on quality and query performance.
- Support data engineers across delivery teams through quality reviews and constructive feedback.
- Collaborate with project teams to deliver outcomes aligned with departmental and program priorities.
- Participate in agile delivery, including in-person attendance at quarterly agile ceremonies and key team events.

What We’re Looking For:

- Data engineering experience: At least five years’ experience as a data engineer, supported by relevant qualifications or training.
- ETL and ELT delivery: Strong experience developing solutions for large or complex data movement, transformation and visualisation, particularly in cloud environments.
- Performance optimisation: Experience preparing data for productive querying in cloud compute engines, including Spark, graph databases and Azure SQL.
- Automated ingestion: Experience sourcing and ingesting data from Oracle, Ingres, Azure and SQL Server environments.




- Analytics‑ready data: Experience transforming data into Parquet and Delta formats for advanced analytics and AI use cases.
- Power BI: Ability to analyse complex datasets and design visualisations suited to the intended audience.
- Communication and collaboration: Strong written and verbal communication, relationship‑building and negotiation skills.

Nice to Have:

- Experience using Azure Data Factory and Databricks together.
- Knowledge of data lake and lakehouse architectures.
- Experience with ArcGIS Enterprise.

Why Join:

- Deliver data engineering solutions that support decision‑making across a federal government department.
- Work across Azure and Databricks within an established agile team.
- Combine hands‑on engineering with technical leadership and quality oversight.
- Secure a 12‑month engagement with the possibility of two further 12‑month extensions.

Citizenship and Security Clearance:

Applicants must be Australian citizens and hold, or be eligible and willing to obtain, Negative Vetting Level 1 (NV1) clearance.

About the Client:

Our client is a Federal Government organisation delivering nationally significant scientific data, digital infrastructure and earth observation capabilities. Their work supports government, academia and industry through access to satellite imagery,



spatial data and digital tools that help identify and understand physical changes across Australia and the Indo‑Pacific.

They are seeking an experienced Lead Data Engineer to join a specialist Data Operations team supporting the maintenance and delivery of scientific products and infrastructure capabilities.

As the Lead Data Engineer, you will work across data management, IT systems and earth observation product support, providing both hands‑on engineering expertise and technical leadership.

The position has a strong focus on cloud‑based data engineering, orchestration, containerisation and Python development, while ensuring security is embedded throughout solutions and delivery pipelines.

Key Responsibilities:

- Designing, developing, validating, maintaining and optimising machine learning workflows through orchestration, testing and documentation.
- Supporting the development and maintenance of data sourcing, ingestion and transformation pipelines.
- Contributing to the development, testing and maintenance of the Open Data Cube code base.
- Implementing, maintaining and improving automated testing and deployment pipelines within AWS environments.
- Providing technical leadership across software development and championing secure, high‑quality engineering practices, tools and standards.
- Supporting knowledge transfer and upskilling of Earth Observation Scientists and providing guidance on improvements to existing algorithms.
- Embedding security tools and practices within systems and CI/CD pipelines.
- Helping ensure services and components remain available and

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