Senior Data Engineer

The Benefits Integrity Division (BID) is seeking a Data Engineer to support the delivery of the BID Analytics Project and contribute to the development of modern data platforms that strengthen the integrity of Australia's health payments system. Working within the Risk Analytics Section, the Data Engineer will support the implementation of the BID Analytical Needs Implementation Roadmap, which aims to optimise data insights, reduce inefficiencies and consolidate analytical capabilities currently distributed across multiple platforms.   The Data Engineer will design, build and maintain data pipelines, integration frameworks and cloud-based data solutions that support the collection, transformation, storage and delivery of data from sources including the Medicare Benefits Schedule (MBS), Pharmaceutical Benefits Scheme (PBS) and other health-related datasets. The role will ensure data is reliable, secure and accessible to support analytics, reporting, compliance and operational decision-making.   Working closely with business and technical stakeholders, the Data Engineer will translate business requirements into scalable data solutions, integrating diverse data sources and improving data quality and accessibility. The successful candidate will collaborate with data scientists, analysts and operational teams to enable advanced analytics, reporting and risk detection capabilities across the Division.   Through the application of contemporary data engineering practices, automation and cloud technologies, the Data Engineer will help improve access to trusted data, reduce manual effort and support the Division's ability to identify, prevent and respond to integrity risks across Australia's health payments system.  Key duties and responsibilities Work independently to deliver complex data engineering projects and business outcomes, applying established standards, technical expertise and professional judgement in unfamiliar or evolving environments.  Design, build, maintain and optimise secure, scalable and reliable data infrastructure, platforms and cloud-based solutions that support the collection, storage, transformation and delivery of data for analytical and operational purposes.  Develop, implement and enhance ETL/ELT pipelines and data integration frameworks, ensuring efficient and reliable movement of data across multiple systems, platforms and data sources.  Integrate structured, semi-structured and unstructured data from diverse sources, maintaining high standards of data quality, consistency, accessibility and integrity.  Design and maintain data models, schemas and storage solutions that support analytical, reporting and operational requirements while ensuring scalability and maintainability.  Monitor, troubleshoot and optimise data pipelines, database performance and cloud environments to improve efficiency, reliability and system performance.  Collaborate with business and technical stakeholders to gather requirements, translate business needs into data engineering solutions and support the delivery of analytical, reporting and data science capabilities.  Work closely with data scientists, analysts and operational teams to ensure data platforms and pipelines support advanced analytics, machine learning, reporting and risk detection activities.  Apply contemporary data engineering tools and technologies, including SQL, cloud platforms, enterprise data warehouses and analytics platforms, to deliver sustainable and fit-for-purpose solutions.  Implement and maintain data governance, security and compliance controls, ensuring data is protected, appropriately managed and aligned with organisational and legislative requirements.  Undertake quality assurance activities, including reviewing code, data pipelines and technical solutions, to ensure outputs meet agreed standards for accuracy, reliability and maintainability.  Maintain technical documentation, data dictionaries, architecture artefacts and operational procedures, ensuring organisational knowledge is captured and shared effectively.  Identify opportunities to improve data architecture, automation and engineering practices, introducing contemporary approaches that enhance organisational capability and support continuous improvement.  Build and maintain productive relationships across multidisciplinary teams, provide clear updates on project progress, risks and issues, and contribute to a collaborative and inclusive working environment.  Share expertise and lessons learned, support capability development within the Section and promote best-practice data engineering approaches across the Division.  Criteria The buyer has specified that each candidate must provide a one page pitch to address all criteria specified. This is equal to 5000 characters. Essential criteria 1. Demonstrated experience with data analytical platforms such as R Shiny, SAS, Power BI, Qlik 2. Demonstrated experience in cloud-based data structures, storage solutions, and architecture, with experience in designing and implementing cost efficient and secure data solutions. 3. Demonstrated experience in developing, implementing, and optimising ETL pipelines and automating data workflows using scripting languages tools. 4. Proven ability to collaborate effectively within a team and across various areas of an organisation, with experience in data governance and ensuring compliance with data protection regulations. 5. Demonstrated experience with SQL, SAS, R or Python for programming. 6. Ability to optimise database performance, document data processes, and communicate technical concepts clearly to non-technical stakeholders. Opportunity summary Sellers can submit Up to 3 candidates Number of sellers invited Fewer than 5 Number of candidates submitted Fewer than 10 Send us feedback About Accessibility Privacy Terms of use Disclaimer and copyright An initiative of the Digital Transformation Agency The Australian Government acknowledges the Traditional Owners of Country throughout Australia and acknowledges their continuing connection to land, waters and community. We pay our respects to the people, the cultures and the Elders past and present. © Commonwealth of Australia