About the Branch The role of the Transformation Office is to provide insights, solutions and advice to decision makers, policy makers and the market to improve scheme operations and position the agency as a modern, efficient and effective regulator. Branch objectives: Provide advice, capability uplift and support to the agency's transformation Program design and implementation that is viable, desirable and sustainable. Create a renewed focus on synergising interdependencies, maturing governance, driving business transition and benefits realisation through the CER Change Program. Support the Chief Data Officer and the agency to create a data-driven culture that identifies external trends to inform strategic decisions and support business transformation. Model and embed best practice across portfolio, program and project management in delivering our strategic objectives and outcomes for the agency. About the Section The Data Innovation and Tools section supports the agency to unlock the potential of our data to drive innovation and compliance for the agency. Specific responsibilities include: Support the Chief Data Officer and the agency in delivering the Data and Reporting Strategy to improve data governance. Support business areas to improve data transparency under the agency's open data policy. Promote and facilitate sharing of scheme data across Commonwealth agencies. Provide a point of liaison between the Digital Services branch and business areas on the delivery of data services infrastructure under the Data Services Roadmap. Build agency analytics capability, and utilise data analytics and geospatial analytics to: Support the integrity of agency schemes by detecting, predicting and preventing non-compliance. Provide insights and evidence to decision-makers and other stakeholders on the behaviour of our clients and the trends and outcomes in our schemes. Identify and deliver business improvements and efficiencies. Support innovative approaches to reduce regulatory burden, support self-service approaches, improve efficiency and encourage compliance with our schemes - by: Working with business areas to identify, prioritise and implement innovative approaches to scheme and participant needs or problems. Provide targeted skills and resources to consult on, design, build and/or roll out strategic initiatives that result in improvements to internal processes, data collection, client compliance, and communication related to scheme operations. The key duties of the position include Duties of the APS Level 6, Data Engineer will include but are not limited to: Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure. This includes setting up data pipelines, configuring data connectors, and ensuring data integrity during the ingestion process. Work with various data storage options offered by Microsoft Azure, including Azure SQL Database, Azure Data Lake Storage, Azure Cosmos DB and Azure Blob Storage. Oversee designing data storage systems that scale, perform, and are economical enough to satisfy the business requirements. Develop and implement data integration processes, frequently using Azure Data Factory, to extract, transform, and load (ETL) data from various sources into data warehouses or data lakes ensuring the data is efficiently cleaned, converted, and loaded. Manage work through data operations using Azure DevOps, GitHub and Agile tools and approaches. Provide comprehensive and expert advice on complex topics to key stakeholders and team members in non-technical contexts. Provide accurate and specialised advice including identifying, anticipating problems and contributing to finding effective solutions. Develop and maintain collaborative relationships with stakeholders and contribute to a positive team environment. Develop, organise, coordinate, plan and prioritise projects and/or tasks effectively. Supervise and support the development of a small team, if required. Qualifications/ Experience Our ideal candidate will have: Demonstrated ability to explain complex topics to stakeholders and team members who may not have a technical background by articulating findings, consultations, and present information in a clear and concise manner. Experienced in identifying complex issues, create effective solutions, and anticipate potential problems and take proactive steps as preventative measures. Have demonstrated ability to manage projects or tasks, which requires planning, organising, and prioritising work effectively. Built expertise and technical knowledge to understand the business operations for effective decision on how to collect, analyse and interpret data. Ability to understand and adhere to ethical and best-practice guidelines when working with data, such as maintaining privacy, security and sensitivity of data. Willingness to learn and maintain knowledge of the latest tools, technologies and best practices. Essential Experience in data engineering, including delivering ETL solutions that support critical business decisions. Proficient with Python or R, Apache Spark, SQL coding for analysing and manipulating data. Demonstrated in-depth understanding of data base infrastructure and cloud data solutions, preferably Azure suite (Synapse, Data Factory, Dataverse, SQL, D365, Gen II Data Lake, Analysis Services, PowerBI, Purview). Experience in DataOps and/or DevOps Repos & Pipelines, using Github, CI/CD and attribute-based Access Control and deployments for Power BI.
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