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Principal Data Engineer

Queensland Government•Brisbane, Brisbane Region
Full-timeLead
👁️ 0 views•📝 0 applications•Posted 9/20/2026•Expires 10/21/2026
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Job Description

About us We have a vision that our communities will be safe and supported by fair and ethical public institutions with a focus on those matters of highest threat to the Queensland community. As an organisation we are committed to this vision and as such our values of people, accountability, integrity, courage and excellence underpin everything we do at the CCC. What we offer At the CCC our people have access to a range of employee benefits that promote career development, enhance employee wellbeing and encourage a healthy and balanced work and home life. When you join the CCC you can access the following benefits: - salary packaging- 12.75% superannuation- flexible work options, including working from home- access to paid parental leave- accrued time off- opportunity to purchase leave- 17.5% annual leave loading- health and wellbeing program- study assistance- access to a wide variety of training opportunities- free annual influenza vaccination- six star rated inner city location close to public transport About you Appointments in the CCC are merit-based and will be assessed by looking at what you have done previously, the knowledge, skills and experience you have built, your potential for development, and your personal qualities which align with the leadership competencies and the CCC's values. Possession of tertiary qualifications relevant to the role is highly desirable (e.g. Data engineering, data science, information technology etc). Qualifications acquired from an overseas educational institution will only be accepted where the qualification has been recognised to an equivalent level in accordance with the Australian Qualifications Framework. For this role, we will consider how well you demonstrate the following: Essential Experience: * At least two years of demonstrated experience in data engineering. * Experience with Azure Data Factory, Azure SQL, Azure Data Lake, and Azure App Service is required. * Building and maintaining data pipelines for data integration, processing and ensuring data quality and accuracy through testing and validations. * Ability to work with structured, unstructured, and semi-structured data. * Understanding of common data warehouse modelling and schema design principles, including Kimball, and Inmon. * Experience monitoring and maintaining data warehouse (Azure platform) environments, including defining optimisation approaches to improve security, performance or cost. * Demonstrated experience supporting machine learning workflows by building scalable data pipelines, enabling feature engineering, and collaborating with data analysts to deploy and integrate models within data infrastructure. Beneficial Experience: * Good communication skills, including effective report writing, and the ability to verbally brief stakeholders. * Knowledge of Dev-Ops processes (including CI/CD) and Infrastructure as code is preferred. * Experience with machine learning and business intelligence is highly regarded. * Experience in deploying applications into production environments with code packaging, testing, deployment, and release management. * Experience working in an environment with strict information security and privacy requirements. * A versatile team player excelling in both independent work and collaborative efforts within a team to achieve objectives. How to apply For more detailed information, including what is required to demonstrate your suitability for the role, refer to the attached role description. Pre-employment vetting forms a part of our selection process - you may be asked to provide detailed personal particulars and private interests information. For more information about our security vetting process please refer to How to apply | CCC - Crime and Corruption Commission Queensland Aboriginal and Torres Strait Islander peoples are encouraged to apply.

Required Skills

AzureCI/CDCommunicationCybersecurityData AnalysisData EngineeringData ScienceData WarehousingLeadershipMachine LearningReport WritingSQL

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