Enterprise Data Architect

Our client is looking for an Enterprise Data Architect to provide leadership for data architects and data developers, while leveraging subject matter experts as required. This person strengthens the impact of, and provides recommendations on, business information that will need to be available and shared consistently across the organization through the identification, definition, and analysis of how information assets aid strategies and business outcomes. The client’s Enterprise Data Architect is responsible for discovering the data and analytics requirements for all enterprise-wide data uses.

• Responsible for ensuring the client’s enterprise data is architected in a manner that is in compliance with MDOT’s data governance and data security requirements and promotes reliable and consistent data through effective data management practices and sound design.
• The Enterprise Data Architect, in collaboration with the Enterprise Solutions Architect, Enterprise Infrastructure Architect, and Data Engineering and Integration Lead will design the data frameworks such as enterprise data protection, Master Data, and Reference Data.
• Develop and propagate data subscriptions and standards to the development areas, conduct testing and implementation of data services components, and trains development staff on their use.
• Responsible for data services developer tools and mentoring senior development staff on correct tool usage and data modeling standards.
• Influence information strategy: By partnering with MDOT’s Office of Enterprise Information Management (EIM), and through the rationalization of the information value chain, the MDOT Enterprise Data Architect will provide strategic recommendations to maximize the value of information assets via their creation, access, and use.
• Maximize value derived from data and analytics: Foster value creation using the organization's data assets, as well as the external data ecosystem. This includes aiding value creation through data exploitation, envisioning data-enabled strategies, as well as enabling all forms of business outcomes through analytics, data and analytics governance, and enterprise information policy.
• Surface information priority: Assess 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.
• Enhance decision making: Use tools such as business information models to provide 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. Assist decision design.
• Enable effective data and analytics governance: Suggest who can take what actions with what information, and under what circumstances. Assist data and analytics leaders, and business and IT leadership in developing information governance processes and structures. In coordination with the MDOT CIS.
• Conduct data modeling: Create, manage, and review data models in all their forms, including conceptual models, relational database designs and others.
• Mentor tech leads on data modeling and data flow diagraming standards and correct tool usage.
• Participates in data model and data flow diagram structured walkthroughs ensuring data models are in alignment with MDOT information governance policies as well as sufficiently reviewed and approved. providing data modeling and design guidance to teams, including identification of data entities, data dependencies, and data relationships.
• Manage risk: Aid the definition of data classifications to allow information assets to be immediately identified and proactively managed as more information becomes federated in a digital economy. Responsible for reviewing results of developer impact analysis findings, ensuring accuracy and completeness, and updating findings as needed. Participates in major problem resolution for data-related issues. Advise and consult on data related audits.
• Enable enterprise information management: Ensure that the architecture is used as a lens and a filter to identify, prioritize and execute the data and analytic initiatives with clear line of sight to enterprise strategies and business outcomes.
• Secure data and analytic assets: Aid in the analysis of data and analytics security requirements and solutions, and work with the Chief Information Steward (CIS) to ensure that enterprise data and analytics assets are treated as protected assets.
• Improve enterprise data performance: Aid 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.

• 7 years - Experience in IT and enterprise data architecture and at least four years in information system design.
• In-depth experience of designing and implementing information solutions.
• 5 years - Experience as a data analyst
• Experience with ESRI, GIS software, geodatabase management application
• Understanding of common information architecture frameworks and information models.
• Understanding of metamodels, taxonomies and ontologies, as well as of the challenges of applying structured techniques (data modeling) to less-structured sources.
• Knowledge and proven skills in MS SQL Server and/or Oracle SQL
• Experience with distributed management and analytics in cloud and hybrid environments. Also, an understanding of a variety of data access and analytic approaches (for example, microservices and event-based architectures).
• System integration experience, including interface design, and familiarity with web-oriented architecture techniques.
• Bachelor's degree in computer science, information systems or a related study (or equivalent project-related experience).

• Hands-on experience implementing data and analytics management programs
• Familiarity with data science concepts, as well as MDM, business intelligence, and data warehouse design and implementation techniques.