Enterprise Architecture Sr; Enterprise Data Architect Sr

Position Overview

As a senior Enterprise Architect within PNC’s Enterprise Technology Architecture organization, you will be based in Pittsburgh, PA or Strongsville, OH or Dallas, TX or Phoenix, AZ or Lakewood, CO. You will collaborate with key data and technology stakeholders to build out the enterprise data architecture practice and execute PNC’s data strategy.

• Build data‑strategic plans that guide business and technology leaders and meet data technology needs.
• Create usable architecture artifacts that measure and demonstrate progress against the strategy.
• Guide stakeholders with their data priorities by developing metrics and ensuring objectives are met.
• Measure progress against strategic data objectives and produce results analysis with follow‑up.
• Articulate the business impact of complex data flows and data‑duplication decision making.
• Create data reference architectures that establish data consumption standards and patterns.
• Identify and document data flows that form the basis for optimizing data lineage and retention.
• Produce data architecture analysis with supporting artifacts for technology recommendations.
• Develop architecture patterns that drive common data flows and standardized integration.
• Identify, assess, and resolve complex data definitions and semantic structure inconsistencies.
• Lead the development of data modeling standards, best practices, and guidelines.
• Design data entity and flow models that enable operational reporting, analytics, and modeling.
• Maintain comprehensive inventory of contextual, conceptual, logical, and physical data models.
• Ensure data models comply with data architecture policies and standards with validation checks.
• Oversee metadata, master data, and reference data management to ensure data consistency.
• Design ontologies and semantic models for driving the adoption of data mesh and virtualization.
• Drive alignment of data ontologies and data semantics that support regulatory requirements.
• Serve as the principal authority for metadata standards, collaborating with Data Owners/Stewards.
• Establish enterprise standards for ontology modeling, naming conventions, and data taxonomies.
• Work with enterprise and solution architects to implement data observability capabilities.
• Guide how data products align to the data standards and work closely with data architects.
• Partner with architecture teams to align solution architectures with data architecture standards.
• Champion the definition and adoption of semantic layers that drive remediation best practices.
• Provide thought leadership and mentorship to translate complex data strategies and concepts.
• Measure progress against objectives with follow‑up when results are achieved or not achieved.
• Ensure adherence to best practices, data principles, and semantic data governance.
• Define auditability and traceability standards for financial and operational data with metrics.
• Establish, document, and maintain governance practices for data modeling and architecture.
• Act as a subject‑matter expert for enterprise architecture projects, guiding teams and clients.
• Leverage enterprise standards, processes, and methodologies to shape strategy and transition plans.
• Provide guidance on technical service capabilities, design attributes, and enterprise profiles.
• Maintain stakeholder relationships, addressing requirements and providing client consultations.
• Support enterprise architecture by directing teams in baseline, target, and roadmap development, transition planning, system and security management, and segment architecture.

• TOGAF certification or equivalent enterprise architecture experience.
• Experience in large, complex enterprise environments.
• Familiarity with both operational and analytical data platforms.
• Hands‑on experience executing Data Architecture within a TOGAF or TOGAF‑like EA framework.
• Strong understanding of baseline/target architecture, gap analysis, and transition planning.
• Experience working within formal architecture governance processes.
• Ability to translate business needs into data architecture outcomes.
• Strong written and verbal communication skills.
• Proven ability to influence decisions without direct authority.