Data Analyst

Data Analysts the design, analysis and delivery of relevant, trusted and objective statistics and data -related insights. The Data Analyst should have experience in the areas of SAS migration/upgrades, data quality profiling, and exposure to metadata management practices and tools such as Aristotle or other data cataloguing solutions. The role assists with the management of the organisation's data assets to ensure data is discoverable, understood and of appropriate quality. The analyst uncovers and where appropriate documents customers' data requirements and is able to: Conduct data quality analysis and curate/ transform data present in DataLake/Teradata to support reporting needs Generate data quality profiles using SAS data management tools, Teradata and/or Data Lake Use SAS tools such as QKB to identify duplicate records and implement matching scenarios Develop reporting to visualise data quality profiling results and to support the use and management of data catalogues using tools such as Power BI and Tableau. Senior Data Analysts work under the limited direction of senior staff. They exercise both initiative and judgement in the interpretation of policy and in the application of practices and procedures. Decision making is dependent on judgement, skills and knowledge. Senior Data Analysts manage and organise their own work in the context of competing priorities, including contributing to business planning, changes in workplace practices and business improvement strategies. Duties may include some or all of the following: • Evaluating, defining, integrating and organising data coming from multiple operational systems • Performing administrative, technical and customising tasks in the data environment • Controlling and assisting with the data management process, including loading, creating maintaining, analysing and distributing data • Resolving data integration issues related to data in their area of expertise • Developing and maintaining reports, dashboards and other visualisations to support data governance and data management processes • Collaborating with stakeholders to resolve issues and ensure effective, timely implementation of projects • Monitor workloads to ensure business goals are achieved • Assist in the processing of data, including matching and maintaining specific object data • Develop data standards and provide input to strategy for the solution • Assist in development of, and execution of, data quality programmes • Contribute to the development and implementation of improvements and best practice in processes and procedures • Contribute to relevant business and people planning, and develop local strategies to improve against key performance measures • Prepare correspondence such as reports, corporate and technical documentation for review by executive level staff • Resolve or escalate issues as required and suggest alternative approaches • Exercise appropriate delegation in accordance with legislation and guidelines Technical skills 1. Experience in data analysis including data governance and data management in government/public sector or industry equivalent. 2. Experience in at least one of the following tools - Data Lake, HUE, SAS, SQL, Aged Care, EDW/Teradata, Mainframe, Tableau. 3. Working knowledge of Data Lake, Hadoop, EDW, Cloudera and Hue. 4. Experience in designing and delivering data analytics solutions for large and complex projects. Mandatory Criteria 1. Business intelligence: Level 3 (SFIA) Sources and prepares data for analysis and performs standard business intelligence analysis activities. Creates and delivers standard reports in accordance with stakeholder needs and conforming to agreed standards. Investigates the need for new or revised business intelligence analysis. Contributes to the recommendation of improvements. Engages with stakeholders under direction. 2. Business situation analysis: Level 5 (SFIA) Plans, manages and investigates business situation analysis where there is significant ambiguity and complexity. Advises on the approach and techniques to be used for business situation analysis. Ensures holistic view adopted to identify and analyse wide -ranging problems and opportunities. Engages and collaborates with a wide range of stakeholders, including those at the management level. Gains agreement from stakeholders to conclusions and recommendations. Contributes to definition of organisational standards and guidelines for business situation analysis. 3. Data communication: Level 3 (DCF) Can develop and deliver advanced level narrative to communicate insights drawn from complex data sources and outputs Maintains understanding of new trends and innovations relating to data communication (including Artificial Intelligence -based technologies) and develops skills in these where relevant Understands the importance of translating technical concepts into non -technical language, and can adapt communication effectively for a range of audiences. Can use innovative approaches to improve the process of summarising data into meaningful narratives Uses high quality analytics and visualisation to communicate insights from data Can effectively listen to technical and business stakeholders, and understand and interpret their data needs 4. Data management: Level 4 (SFIA) Devises and implements master data management processes for specific subsets of data. Assesses the integrity of data from multiple sources. Provides advice on the transformation of data from one format/medium to another. Maintains and implements information handling procedures. Enables the availability, integrity and searchability of information through the application of formal data and metadata structures and protection measures. 5. Data modelling and design: Level 4 (SFIA) Investigates enterprise data requirements where there is some complexity and ambiguity. Plans own data modelling and design activities, selecting appropriate techniques and the correct level of detail for meeting assigned objectives. Provides advice and guidance to others using the data structures and associated components. 6. Data outputs, products or services: Level 3 (DCF) Has expert knowledge about the production of a data output, product or service Provides expertise in developing new products or data services to meet evolving requirements, needs and opportunities. Can build the capability of others in the delivery of data outputs, products or services 7. Data visualisation: Level 4 (SFIA) Applies a variety of visualisation techniques and designs the content and appearance of data visuals. Operationalises and automates activities for efficient and timely production of data visuals. Selects appropriate visualisation approaches from a range of applicable options. Contributes to exploration and experimentation in data visualisation. 8. Database design: Level 3 (SFIA) Interprets installation standards to meet project needs and produces database or data warehouse component specifications. Develops appropriate physical database or data warehouse design elements, within set policies, to meet data requirements. 9. Identify research questions: Level 3 (DCF) Uses a range of techniques to assess data needs and identify gaps, towards the formulation of appropriate research questions 10. Integrate data: Level 2 (DCF) Can perform data integration using standard tools and can implement quality controls Knows where to obtain expert advice on data integration as needed Is able to understand and amend existing code (programming language) to integrate data Can assess datasets' suitability for linkage and extract appropriately prepared datasets 11. Programming/software development: Level 3 (SFIA) Designs, codes, verifies, tests, documents, amends and refactors moderately complex programs/scripts. Applies agreed standards and tools to achieve a well -engineered result. Monitors and reports on progress. Identifies issues related to software development activities. Proposes practical solutions to resolve issues. Collaborates in reviews of work with others as appropriate. 12. Statistical data analysis: Level 3 (DCF) Contributes to the development of new functionality for statistical analysis applications, which enables new ways of doing things Can write custom scripts and code in a statistical computing language to conduct complex analytical tasks Maintains understanding of new trends and innovations relating to statistical data analysis (including Artificial Intelligence -based technologies) and develops skills in these where relevant 13. Subject matter expertise: Level 3 (DCF) Is an expert resource on the subject matter area associated with data use, including understanding and influencing the effective use of the data within that subject matter area and the relationship between that use and other data use contexts