To work within a team of architects providing support to core infrastructure and business-led projects, offering specific data architecture expertise to solution and enterprise architects.
Role Overview
The appointed person will be an integral member of the Architecture Team, responsible for ensuring all initiatives explicitly consider data as part of their approach and that all elements of the data lifecycle are adequately provisioned. They will also be involved in designing and implementing the enterprise data strategy to support current and future business needs. Collaboration with Business and IT stakeholders at all levels is essential to ensure the enterprise data strategy adds value to the business.
Major Tasks and Activities
1. Develop and evolve the enterprise data strategy to support corporate objectives.
2. Act as a key stakeholder and advisor in new strategic data initiatives, ensuring alignment with the enterprise data strategy.
3. Influence core system development decisions regarding data storage, integration, aggregation, and access across the landscape.
4. Contribute to creating principles to ensure data integrity across systems such as ERP, BI, Data Warehouse, and external interfaces.
5. Guide the organization in making informed business, technology, and data decisions, emphasizing reuse, sustainability, and scalability to maximize value and minimize risk.
6. Align the Data Architecture strategy and roadmap with business and technology strategies.
7. Build and maintain Enterprise Architecture artifacts like Entity Relationship Models, interface catalogues, and taxonomies for data traceability.
8. Design enterprise-level data ontologies supporting key business initiatives such as asset management, training, and MRO.
Qualifications and Experience
1. Experienced IT professional with a bachelor’s degree in information technology or a related field.
2. Proven experience in system architecture and data solutions, including data warehousing, data transformation, and supporting technologies like Azure Data Factory and Data Lake.
3. Strong technical, analytical, and problem-solving skills, with expertise in data modelling (logical, physical, semantic, and integration models), normalization, OLAP/OLTP principles, and entity relationship analysis.
4. Excellent communication, interpersonal, leadership, and motivational skills.
5. Experience in architecting data solutions across hybrid (cloud and on-premise) platforms and designing solutions for external accreditation bodies.
6. Familiarity with industry best practices in data architecture, data engineering principles, and supporting technologies such as RDBMS, NoSQL, Cache, and In-memory stores.
7. Experience working with environments complying with standards like JSP 604 and supporting accreditation processes.
8. Proficiency with architectural toolsets such as Sparx EA, Lean IX, or System Architect.
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