Lead Data Engineer

Data Engineers prepare raw data for analytical or operational uses. They make data accessible so that it can be used for optimisation, delivery of services and enhanced analytics solutions. The Data Engineers will design, build and maintain data products, services and platforms that support the agency’s operational, analytical and business intelligence needs. They will transform and manage data throughout the data lifecycle to ensure data assets are secure, reliable, accessible and fit for purpose. The Data Engineers will work collaboratively with business and technical stakeholders to deliver scalable data solutions, support evidence-based decision making, and contribute to the continuous improvement of the agency’s data ecosystem. Data Engineer Experts will provide technical leadership in the design, delivery and optimisation of complex data engineering capabilities. They will drive improvements to data services, governance, security and operational performance, while resolving complex technical challenges. The Data Engineer Experts will influence stakeholders, contribute to strategic initiatives and organisational outcomes, and provide expert advice and guidance to support the delivery of high-quality data engineering solutions. Technical Skills: • recognise and initiate opportunities to re-use and align data models • undertake data profiling, source system analysis and synthesis, and support the end use of data • use metadata repositories to support complex data and systems integration impact analysis and business outcomes • design, build and test complex or large data products using agreed standards, technologies and access methods to deliver repeatable, reusable solutions and strengthen team capability in data integration services • apply expert skills in data quality, cleansing and validation • promote the strategic data vision through effective work practices and active participation in collaborative forums • translate and present technical information for non-technical audiences. The Data Engineers must have extensive knowledge of: • The ability to apply existing corporate and technical knowledge to maintain business and delivery continuity. • The capability to integrate quickly and contribute effectively within our established delivery environment. • End-to-end data lifecycle practices, including design, build and test phases, and data architecture and modelling concepts for data warehousing and data lakes. The Data Engineers must also have the ability to quickly obtain knowledge of: • The agency's strategic outlook and direction. • Relevant frameworks, legislation, policies and procedures. • Payments, programs and services administered by the agency relevant to work area. • The agency’s privacy, workplace health and safety and security protocols • Relevant knowledge and experience of our systems, platforms, and processes. • A strong understanding of Agency business requirements and outcomes. Key duties and responsibilities Duties may include some or all of the following: • Support in the delivery of data assets by contributing to improving data management capabilities, including building data integration applications that extract. • Transform, and load (ETL) data and metadata into data warehouses + Data Lake (RDBMS/HDFS). • Undertake analysis, design, development, prototyping, testing and maintenance activities in a Teradata EDW environment. • Contribute to building and maintaining automated data integration applications by developing complex SQL programs within a Teradata EDW environment. • Perform analysis of technical requirements to support project evaluation with proposed solutions. • Ensure excellent data quality and high standards in Management Information solutions. • Development of ELT solutions using a variety of industry tools including SQL Assistant, Terada Studio Viewpoint, Pcom and Control-M. • Write/explain technical systems, problems and outcomes using unambiguous language to non-technical staff. • Strong focus on data integrity between source and destinations systems. • Analyse and evaluate complex business process and requirement. • Work with stakeholders to assemble large, complex data sets that meet current and potential business requirements. • Design and implement data flows connecting operational systems, using data analysis and modelling to build, maintain, and optimise data structures that support controlled data extraction for analytics and business intelligence. • Manage the build of data streaming systems, and development of management information solutions. • Manage the design, development and maintenance of enterprise data warehouse, data lake and data engineering solutions. • Lead the optimisation of data extraction solutions, providing technical guidance on complex query and programming functions to deliver data outcomes aligned to stakeholder and agency requirements. • Perform analysis on data and processes to address business questions, identify opportunities for improvement and provide support to staff. • Manage the development of data engineering frameworks and best practices for processes aimed at enhancing the availability, security and performance of data assets. • Review and prepare corporate and technical documentation for review by senior staff. • Provide feedback to staff and stakeholders to improve quality, consistency and accuracy of decision making. • Lead collaboration across cross-functional agile teams to deliver data engineering solutions. • Lead and manage team operations to deliver business and strategic outcomes, setting priorities and allocating resources effectively. • Lead and manage staff to enhance performance and engagement by providing coaching, developing capabilities, managing performance, and supporting health and well-being. • Act with integrity by promoting workplace practices aligned with the APS Values and the APS Code of Conduct. • Exercise delegation in accordance with legislation and guidelines. 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. Data access: Level 2 (DCF) Has a comprehensive knowledge of protocols associated with data access. 2. Data editing: Level 3 (DCF) Is an expert resource on different methods of data editing and advises others Can assess current editing methods critically Can build capability of others in data editing concepts and methods 3. Data integrity and quality assurance: Level 3 (DCF) Is an expert resource in the use of measures for data quality assurance, the interaction of those measures, and their application in conjunction with one another Can advise others on the use of data quality measures to make accurate assessments of data fitness-for purpose (including trustworthiness and accuracy) Is an expert resource on ensuring data integrity across its lifecycle, and advises others 4. Data use and re-use: Level 3 (DCF) Is a leading strategic adviser on the use of organisational data assets Is an expert resource on the design and management of organisational data assets as open data. Promotes re-use and ongoing value of data across wider contexts, in accordance with legislative requirements and organisational guidelines (includes data sharing legislation) 5. Improvement and Innovation - Data processes/systems and tools/products: Level 3 (DCF) Thinks strategically to assess current processes/systems and tools/ products across a broad context Develops improvements where needed and encourages others to think critically about processes/systems and tools/ products relevant to them Advises those leading changes to processes / systems and tools/ products, measures resultant benefits, and makes recommendations Understands the impact of new trends and innovations on organisational data processes, systems and tools, and products Maintains understanding of new trends and innovations relating to data processes, systems and tools, and products within the organisation and externally. Provides technical expertise for systems testing, including validating the quality of the testing approach and results 6. Integrate data: Level 3 (DCF) Can perform and provide expert advice on data integration Can build capability of others in understanding and applying good data integration practice and principles Can write custom scripts and code (programming language) to integrate data Maintains understanding of new trends and innovations relating to integrating data (including Artificial Intelligence-based technologies) and develops skills in these where relevant 7. Value organisational data as assets: Level 3 (DCF) Has a comprehensive understanding of the data assets available to the organisation and understands how these assets contribute strategic value Looks for new ways to obtain value from organisational data assets Can advise on how organisational data assets contribute value in broader data contexts Is an expert resource on the broader and strategic environment when drawing insights from data. Uses this expertise to make informed, evidence-based decisions and recommendations and act accordingly. Opportunity summary Sellers can submit Up to 3 candidates Number of sellers invited More than 10 Number of candidates submitted Fewer than 10 RFQ closing time 02 Weeks 00 Days 12 Hours 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