Department of Veterans' Affairs (DVA) has an insatiable appetite for data and associated insights. From ad-hoc requests for specific information to inform reporting and policy development, to cutting edge modelling to predict future trends, volume, costs, and program efficacy - data is increasingly central to everything we do. The purpose of the Data and Insights Branch is to evolve the way the department produces and uses data, analytics and research, to underpin evidence-based policy development, service delivery and wellbeing outcomes. The branch fosters a culture of curiosity in data and research, establishing processes that enable the department to better understand and serve the needs of veterans and their families. The Data Engineering team is building an enterprise data warehouse, integrating data from multiple sources into curated data products that are used for a variety of purposes including standard business reporting, advanced analytics, simulation modelling and predictive analysis. Our primary purpose is to ensure that source system data is well understood, documented for business use, modelled into consistent formats and structures, and to build products that enable business teams to understand their business and to drive decision making. We also provide technical support for proof of concept projects, trialling new ways of working with data and technology especially in cloud infrastructure. We work closely with the Visualisation team and ICT teams to improve data within DVA. Our current focus for recruitment is across technical analysts roles, data engineers and data modellers. We are particularly interested in candidates with skills in Amazon Web Services and Microsoft cloud environments, with a focus on Azure Data Factory and Microsoft Purview Data Governance and Compliance tools, as well as Python coding experience. An understanding of third normal form and star schemas modelling techniques, Atlassian Cloud (Jira and Confluence) and Gitlab would also be of value. We are seeking an experienced Data Analyst to assist in the development of our Enterprise Data Warehouse (EDW). The ideal candidate for the Data Analyst role will possess a strong analytical mindset and extensive experience in examining and profiling source system data to understand its nature and structure. They will be adept at developing data engineering specifications to integrate data into the enterprise data warehouse, ensuring alignment with existing patterns. This individual will collaborate effectively with data engineers to comprehend current data transformation processes and work closely with data modelers to understand and enhance existing data models. A proactive approach to problem-solving is essential for success in this role. The key duties of the position include Evaluate and profile data sources and legacy data products, to identify the most suitable data to meet new requirements and determine ETL rules. Design and document ETL rules and mapping rules. Write and optimise SQL queries to retrieve data. Work with Data Modellers to design a model that will meet the needs of users, while maximising re-use. Plan, document and execute testing of data products, and ETL processes, and contribute to other quality assurance activities. Create practical and actionable plans to address complex data issues, and be able to explain these to users and other stakeholders. Work with the team to improve processes, determine standards and devise technical solutions for the ongoing development of the EDW and related tools. Work with Governance and Business to implement privacy and security controls. Work with Engineers, Analysts and Business to implement timelines for integrated EDW data tables. Communicate complex information or specialised content clearly, accurately and precisely for different stakeholders in person and in documentation.