Job Description
Remote is seeking Lead Data Modellers to join the team in ASD. The Lead Data Modellers will have in-depth knowledge of data warehousing, modelling techniques covering conceptual, logical and physical representations of transactional, analytical and big-data processing systems. as well as expert communication skills. (LH-02771)
Role Description
Candidates will bring the following attributes:
- Strong written and verbal communication skills;
- Desire to be accountable for their actions;
- Certifications or training evidence in Data Modelling;
- Demonstrated knowledge of Commonwealth frameworks, including ICT frameworks and Resource Management and data storage and warehousing solutions;
- Strong stakeholder management skills;
- Demonstrate leadership behaviours;
- Willing to challenge the traditional ways of doing business;
- Thrive in dynamic environments and comfortable with ambiguity;
- Outcome-focused mindset; and
- Adaptability, resilience, flexibility and teamwork, including regionally dispersed teams, if applicable.
Key duties and responsibilities:
- Undertaking work that is moderately complex to complex and/or sensitive in nature, under limited direction, utilising expertise and knowledge within the area of data modelling.
- Analysing and translating business needs into long-term solution data models.
- Evaluating existing data systems.
- Working with the development or Agile Delivery team to create conceptual data models and data flows.
- Developing best practices for data coding to ensure consistency within the system.
- Employing data modelling techniques to develop analytical solutions and make recommendations to business stakeholders.
- Establishing sustainable automatic analytical processes.
- Collaborate with stakeholders and data professionals to identify and support process improvement opportunities within data governance and quality frameworks.
- Reviewing modifications of existing systems for cross-compatibility.
- Implementing data strategies and developing physical, conceptual and logical data models.
- Updating and optimizing local and metadata models.
- Evaluating implemented data systems for variances, discrepancies, and efficiency.
- Troubleshooting and optimising data systems.
Essential criteria
- SFIA DTAN 5: Sets standards for data modelling and design tools and techniques, advises on their application and ensures compliance. Manages the investigation of enterprise data requirements based upon a detailed understanding of information requirements. Coordinates the application of analysis, design and modelling techniques to establish, modify or maintain data structures and their associated components. Manages the iteration, review and maintenance of data requirements and data models.
- SFIA DATM 5: Devises and implements master data management processes. Derives data management structures and metadata to support consistency of information retrieval, combination, analysis, pattern recognition and interpretation, throughout the organisation. Plans effective data storage, sharing and publishing within the organisation. Independently validates external information from multiple sources. Assesses issues that might prevent the organisation from making maximum use of its information assets. Provides expert advice and guidance to enable the organisation to get maximum value from its data assets.
- SFIA EMRG 4: Supports monitoring of the external environment and assessment of emerging technologies. Contributes to the creation of reports, technology road mapping and the sharing of knowledge and insights.
- SFIA STPL 5: Supports monitoring of the external environment and assessment of emerging technologies. Contributes to the creation of reports, technology road mapping and the sharing of knowledge and insights.
- SFIA SCTY 3: Applies and maintains specific security controls as required by organisational policy and local risk assessments. Communicates security risks and issues to business managers and others. Performs basic risk assessments for small information systems. Contributes to the identification of risks that arise from potential technical solution architectures. Suggests alternate solutions or countermeasures to mitigate risks. Defines secure systems configurations in compliance with intended architectures. Supports investigation of suspected attacks and security breaches.