Enterprise Architecture Analytics Lead

Role Overview

• Lead a cross-IT initiative to define and integrate core IT data objects into a coherent, governed, and scalable enterprise data foundation.
• Establish a common data model, taxonomy, and standards for critical IT domains, including financial, forecasting and planning data, financial plan versus actuals, IT support and incident management, enterprise architecture, IT service catalog, enterprise capabilities, code, programs and projects, and execution backlog.
• Design and drive agentic AI frameworks and enabling architecture that support cross-domain natural language inquiries, conversational experiences, and chatbot-based access to trusted BoIT data.
• Define the semantic, metadata, and integration foundations required to enable AI agents and natural language interfaces to interpret, retrieve, and relate data consistently across architecture, finance, planning, support, portfolio, and execution domains.
• Partner with stakeholders across enterprise architecture, finance, planning, service management, portfolio management, and engineering teams to align definitions, ownership, quality rules, and data flows.
• Drive end-to-end mapping of relationships across business objects, systems, and processes to improve traceability between strategy, investments, services, applications, capabilities, delivery, and operational outcomes.
• Define and implement standards for data quality, stewardship, metadata, lineage, and lifecycle management across the BoIT ecosystem.
• Identify current-state gaps, redundancies, and inconsistencies across tools and repositories, and shape a pragmatic roadmap toward an integrated future state.
• Translate business and operational requirements into architecture-aligned data and tooling solutions that improve visibility, governance, reporting, and AI-enabled discoverability.
• Enable executive and operational reporting by improving the consistency and accessibility of enterprise data related to planning, financials, support, architecture, and execution.
• Facilitate cross-functional working sessions, decision forums, and governance reviews to build consensus and accelerate adoption of standards and tools.
• Support the evolution of enterprise standards, architecture artifacts, and tool capabilities that strengthen interoperability across the IT landscape.

Requirements

• Bachelor's or BS degree in a specialized field, or equivalent experience in data science, information engineering, information systems engineering, or a related discipline.
• 7+ years of experience with a Bachelor's degree, 6+ years with a Master's degree, or 4+ years with a PhD.
• Strong technical and business communication skills, including the ability to articulate complex ideas to diverse audiences.
• Experience translating business strategy into technology roadmaps, capabilities, architectures, or transformation initiatives
• Experience working with business and technical stakeholders to define standards, align requirements, and implement scalable data solutions.
• Experience leading technical teams or mentoring engineers in adopting best practices and innovative solutions.
• Proven experience in enterprise architecture, data architecture, IT portfolio management, or a related IT strategy and operations role.
• Strong understanding of enterprise data management concepts, including data modelling, governance, metadata, data quality, and master data management.
• Experience designing and/or developing executive-level insights, dashboards, analytics, or decision-support frameworks.
• Strong analytical, problem-solving, and communication skills, with the ability to connect strategic intent to operational execution.

Benefits

• Hybrid work model
• Professional development opportunities