Data Modeling Director

DTCC • Tampa, FL

2d • Hybrid

About The Position

The Director, Enterprise Data Modeling & Architecture Governance is a senior technology and data leader responsible for establishing and advancing DTCC’s enterprise approach to data modeling and ensuring data architecture standards are governed and adopted consistently. The role defines enterprise data modeling strategy, standards, patterns, automation, and governance across conceptual, logical, and physical data models and enterprise data capabilities. It partners with Enterprise Data Architecture, Data Engineering, Data Governance, business data leaders, and application architecture teams to make data a reusable, interoperable, well-governed enterprise asset.

The Director provides leadership across modern data ecosystems, including Snowflake, AWS, operational platforms, analytical environments, and data products. The role connects business semantics, enterprise information models, data products, and physical implementation, translating enterprise data architecture into actionable engineering standards while balancing consistency with delivery speed.

The position also builds and leads an enterprise data modeling and architecture governance capability, develops senior data modelers, influences business and technology leaders, and establishes multi-year roadmaps to improve modeling maturity and reduce structural data complexity. DTCC offers a flexible/hybrid work model of three days onsite and two days remote, with onsite days including Tuesdays, Wednesdays, and a third day selected by the team or employee.

Requirements

• 12+ years of experience in data architecture, data modeling, data engineering, information architecture, or related disciplines, with significant experience at enterprise scale.
• 5+ years of leadership experience managing architects, modelers, or senior technical professionals.
• Deep expertise in conceptual, logical, and physical data modeling.
• Strong understanding of enterprise information architecture, canonical models, semantic modeling, dimensional modeling, normalization, and domain-driven design.
• Demonstrated experience establishing enterprise architecture governance frameworks, standards, and review processes.
• Experience designing modern cloud data architectures; Snowflake and AWS experience preferred.
• Strong understanding of data governance, metadata management, lineage, data quality, master/reference data management, and data stewardship.
• Experience with enterprise modeling and metadata platforms such as erwin, ER/Studio, Collibra, Alation, Informatica, or equivalent technologies.
• Understanding of data products, data mesh, data contracts, event-driven architecture, knowledge graphs, semantic layers, and API-based integration.
• Ability to establish enterprise standards while maintaining productive partnerships with engineering and business teams.
• Ability to translate complex architecture issues into clear decisions and recommendations for executive audiences.
• Strong organizational influence across teams, including where direct reporting relationships may not exist.
• Experience developing strategies, roadmaps, operating models, and investment priorities.
• Ability to develop talent, including coaching senior architects and technical leaders.
• Ability to balance strategic architecture, risk management, delivery velocity, and total cost of ownership.
• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Engineering, or a related field required.

Nice To Haves

• Master’s degree or equivalent advanced experience preferred.
• Relevant architecture or data-management credentials, such as DAMA/CDMP, TOGAF, Snowflake, or AWS certifications, are beneficial but not required.

Responsibilities

• Define and own enterprise strategy for conceptual, logical, and physical data modeling.
• Establish enterprise modeling methodologies, standards, naming conventions, patterns, and reusable reference models.
• Develop and maintain enterprise canonical models and shared business entities for critical data domains, as applicable.
• Connect business concepts, glossaries, logical and physical models, APIs, data products, and analytical datasets.
• Drive adoption of domain-oriented modeling for operational and analytical use cases.
• Establish governance processes to ensure data solutions conform to enterprise architecture principles and standards.
• Lead or provide senior leadership to data architecture review and design governance forums.
• Define practical data architecture guardrails and decision criteria for engineering teams.
• Establish processes to evaluate and document architecture exceptions, technical debt, and remediation plans.
• Partner with Enterprise Architecture and solution architects to align data architecture decisions across business and technology domains.
• Introduce measurable governance practices, including compliance, model reuse, exception aging, and standards adoption.
• Integrate data modeling with the enterprise metadata and governance ecosystem.
• Align data models with business glossaries, catalogs, metadata, lineage, and data-quality controls.
• Partner with Data Governance and Data Stewardship teams to establish consistent definitions for critical data elements.
• Increase automation across modeling, metadata management, governance, and engineering processes where appropriate.
• Advance semantic modeling so organizational data is easier for people and AI to discover, understand, govern, and use.
• Provide architectural leadership for modeling across Snowflake, AWS, traditional platforms, and operational data platforms.
• Establish modeling guidance for relational, dimensional, event-driven, semi-structured, and analytical data patterns.
• Define architecture for data sharing, integration, interoperability, and separation of operational, analytical, and data-product concerns.
• Partner with Data Engineering leadership to translate logical architecture into scalable physical implementations.
• Evaluate emerging approaches such as knowledge graphs, semantic layers, metadata-driven architecture, data contracts, and AI-enabled data management.
• Build and lead a high-performing enterprise data modeling and architecture governance capability.
• Develop senior data modelers, establish career paths, and foster communities of practice.
• Influence senior technology and business leaders on enterprise data architecture decisions.
• Facilitate architecture decisions spanning multiple organizations or data domains.
• Balance strategic architecture objectives with delivery timelines, investment priorities, risk, and operational constraints.
• Establish multi-year roadmaps to improve enterprise modeling maturity and reduce structural data complexity.

Benefits

• Competitive compensation, including base pay and annual incentive.
• Comprehensive health and life insurance and well-being benefits, based on location.
• Pension and retirement benefits.
• Paid time off, personal/family care, and other leaves of absence.
• Flexible/hybrid work model with three days onsite and two days remote.

What This Job Offers

• Job Type: Full-time
• Career Level: Director