WHAT DOES AN ENTERPRISE DATA ARCHITECT DO?

Published: Feb 05, 2025 – The Enterprise Data Architect develops cloud adoption strategies in collaboration with technology and business teams to drive business success. Assesses risks and benefits of cloud technologies oversees governance and ensures alignment with enterprise architecture. Provides thought leadership, establishes best practices, and stays current with industry trends to optimize cloud solutions.

A Review of Professional Skills and Functions for Enterprise Data Architect

1. Enterprise Data Architect Duties

  • Customer Engagement: Engage in telephone and face-to-face conversation to serve customers and give and receive information from customers, staff, vendors, outside consultants, and the public.
  • Technology Usage: Use a computer and similar office technology and tools.
  • Data Entry: Involve reading the screen and keying/typing information.
  • Presentation Skills: Speak and make presentations to individuals or groups on technical subjects related to the job.
  • Interpersonal Skills: Successfully interact with and represent the organization to customers, staff, officers, board members, vendors, and/or the public at all levels.
  • Technical Advice: Provide sound technical advice to customers and other staff in the subject field(s) related to this position.
  • Subject Understanding: Understand and explain various subject matter and consulting concepts, programs, terminology, and methods.
  • Critical Thinking: Reason, judge, compare, calculate, evaluate, decide, and critique such information as written material, numerical data, responses to customer needs, and/or other related work activities.
  • Architecture Development: Practiced in developing Enterprise data architecture within government departments.
  • Migration Expertise: Cloud-based architecture migration and the realization of Service Oriented Architecture (SOA), web and data services, and enterprise data management.

2. Enterprise Data Architect Details

  • Architecture Leadership: Lead the Architecture design of end-to-end enterprise-integrated digital systems that serve multiple business functions.
  • Reference Management: Identify, develop, and manage reference architecture and design patterns for digital applications.
  • Integration Design: Create the design and implementation of integration patterns and data models for strategic business projects.
  • Representation: Represent business projects in architecture governance activities (e.g., Architecture Review Board, Data Governance activities) and address stakeholder concerns.
  • Artifact Management: Own and manage the conceptual/logical/physical architecture artifacts and act as a liaison between architecture and engineering teams to transition the design for delivery.
  • Gap Identification: Identify functional gaps in proposed solutions and initiate technology evaluation.
  • Architecture Development: Design, develop, and maintain data and application architecture - practice, processes, and standards.
  • Project Leadership: Lead architecture projects and perform stakeholder management to ensure strategies are clearly communicated to all stakeholders.
  • Collaboration: Work and coordinate with other Architects to develop and maintain reusable artifacts.
  • Strategy Definition: Define the enterprise data strategy.
  • Requirement Analysis: Perform close communication across business units to gather requirements, design data architecture at enterprise level.
  • R&D Initiative: Be proactive to perform R&D to explore and support the business in migrating to cloud databases, and adopting AI to enable a highly flexible data platform.
  • Technical Leadership: Technically in charge of the overall data processing (Extraction, Transform, and Load).
  • Model Development: Develop Data Lake and build models for forecasting.
  • Presentation Creation: Create dashboards and conduct presentations with senior board members.

3. Enterprise Data Architect Responsibilities

  • Cross-domain Coordination: Work across all domains of IT to ensure alignment on technical direction and leverage common approaches and best practices.
  • Architectural Support: Provide architectural support and consultation to engineering teams to define, design, and implement solution components with engineering teams.
  • Documentation: Document ongoing architectural standards, recommendations, and guidelines.
  • Lifecycle Integration: Integrate key checkpoints in the project lifecycle to maintain the architectural integrity of solution components.
  • Cost Evaluation: Evaluate IT accounting models and identify ways to reduce costs for IT and business leadership.
  • Architecture Planning: Plan the architecture for next-generation business intelligence, data visualization, and analytics leveraging cloud technologies.
  • Governance Participation: Participate in key Enterprise Architecture Governance Teams including the Architecture Review Board (ARB).
  • Technology Education: Identify and educate others on new technologies/methodologies and assess cost and suitability of purpose to the current Data Architecture landscape.
  • Model Development: Develop architectural models that compose all components of an integrated solution and develop multiple views of these models to facilitate communication to business and technical teams.
  • Solution Optimization: Optimize solutions to balance and prioritize security, performance, reusability, and reliability.
  • Technical Assistance: Assist in technical communication and documentation including architectural documentation and technical requirements as well as presentation and knowledge-sharing sessions to develop a clearer understanding between constituencies.

4. Enterprise Data Architect Accountabilities

  • Strategy Development: Partner with technology and business teams to develop a cloud adoption strategy that enables business.
  • Risk Assessment: Assess the benefits and risks of different cloud technologies in the context of the overall enterprise and individual projects.
  • Governance: Govern and oversee cloud resource allocation.
  • Coaching: Coach team members on how best to leverage cloud platforms to deliver business results and enable the technology strategy.
  • Architecture Partnership: Partner with enterprise software architects on cloud application development architecture and configuration to ensure alignment with cloud strategy.
  • Thought Leadership: Provide thought leadership on cloud technologies while maintaining strong relationships with a focus on customer and employee experience.
  • Standards Development: Develop standards and guidance both at the project and enterprise level that fosters consistent and best-fit use of platforms.
  • Documentation: Create and maintain architecture documentation.
  • Documentation Revision: Work with project teams to create and revise necessary documentation as defined by current standards, which includes high-level design specifications and support documents.
  • Design Review: Review design documentation for projects and systems.
  • Industry Trends: Stay up-to-date on industry trends and advancements.
  • Representation: Represent and communicate the mission and values of Farm Credit Mid-America and comply with its conduct policy, security policy, and confidentiality expectations.

5. Enterprise Data Architect Functions

  • Strategy Ownership: Own the enterprise data platform strategy and roadmap for Synopsys.
  • Modernization: Modernize and scale data platform technologies for competitive advantage and growth.
  • Transparency Establishment: Establish transparency and clarity of data platform architecture strategy.
  • Documentation: Document current and future state architecture supporting enterprise data & analytics.
  • Roadmap Development: In partnership with solution and delivery teams, develop business data & analytics capability roadmaps.
  • Framework Visualization: Visualize the enterprise data management framework.
  • Strategy Definition: Define architecture strategy and roadmap for curated data domains, predictive, and advanced analytics.
  • Self-Service Strategy: Define architecture strategy and roadmap for data democratization and self-service capabilities.
  • Governance Establishment: Establish governance of data security and enterprise data architecture practices, working closely with multiple IT, Business Apps, and Security functions.
  • Capability Evolution: Working closely with various technology solution and delivery teams, ensure continuous evolution of data platform capabilities and services in alignment with business strategy.
  • Thought Leadership: Provide data architecture thought leadership to cross-functional teams in the areas of advanced data techniques, including data modeling, data access, data integration, data visualization, data discovery, modern database design, and implementation.
  • PoC Execution: Establish and execute relevant and timely technology PoC and evaluation cycles.
  • Trend Curation: Curate, incorporate and maintain industry trends, vendor relationships, market awareness, network experience, and internal stakeholder inputs.
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