Job Type: Direct Hire
The Enterprise Information Architect is responsible for establishing and executing a vision for the delivery of information and analytic solutions to key stakeholders. The Enterprise Information Architect operates across organizational and technology "silos" to implement a platform capable of providing consumable analytics appropriate to end users’ needs. The Enterprise Information Architect ensures the reliability and sustainability of the Company’s platform. This role works closely with Information Security, Technology and Business Subject Matter Experts, IT and Business Leaders.
- The Enterprise Information Architect (EIA) will be accountable for assisting in the analysis and design of the enterprise information architecture to meet the technical and business requirements. This includes assessment of new products and methods, developing and implementing appropriate IT data practices across multiple applications, operating systems, hardware platforms and delivery models (Cloud and Internally hosted).
- Develops and maintains information architecture for the organization to enable knowledge-worker productivity and improve end-user experience and decision-making capabilities.
- Provides the organization with a future-state view of the information landscape that is unencumbered by the specific data implementation details imposed by proprietary solutions or technologies.
- Insures the data and the information needs of the business are realized through an intentional information architecture. Document the Infrastructure architecture environment and procedures to insure the infrastructure remains cost effective, efficient, and of high quality.
- Re-engineers and maintains an enterprise wide view of the data across all business systems. Analyzes information requirements specified by the user community and designs the required data structures to support those requirements.
- Assesses the benefits and the risks of information by using tools such as business capability models to create an information-centric view to quickly visualize what information matters most to the organization based on the defined business strategy.
- Lead evangelist and influencer for all things ‘data’ at by establishing strong business and technology relationships throughout the company.
- Consults on establishing data classifications and data zoning to allow information assets to be immediately identified and proactively managed as more information becomes federated in a digital economy.
- Champions efforts to improve business performance through enterprise information solutions and capabilities, such as master data management (MDM), metadata management, analytics, content management, data integration, and related information management or information infrastructure components.
- This role will collaborate with several roles aligned to data and analytics like business analysts, information managers, programmers and data stewards as well as business leaders and should be effective at communicating with these different audiences.
Experience(s) that Best Prepares You:
- This role requires a Bachelor’s Degree in Computer Science, Information Systems Management, Analytics or a related study
- The candidate should have a minimum of 10 years’ experience in Information Technology disciplines related to data and information management with progressing increases in responsibility throughout their career.
- Specifically, the incumbent must have at least 2 years’ experience as an Information Architect
- Experience working with supply chain and e-commerce data architectures is highly desired.
- Highly skilled at conceptualizing information through the use of diagrams and models. Effective conceptualization, pattern recognition and design thinking skills.
- Expert level Data-modeling and information classification expertise at the enterprise level.
- System integration experience, including interface design, and familiarity with web-oriented architecture techniques.
- Expert understanding of the differences between relational modeling and object modeling. Expert understanding of meta-models, taxonomies and ontologies, as well as of the challenges of applying structured techniques (data modeling) to less-structured sources.
- Expert knowledge and hands-on experience with MDM, BI, data warehouse design and implementation techniques.