Senior Data Modeler

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Job Title: Senior Data Modeler (Enterprise CDM Owner Cross Asset)
Contract Length: 8+ Month contract(3 days on site/ 2 days remote)
Location: CHARLOTTE NC 28202

Ref# 246114

Seeking a Senior Data Modeler to serve as the internal enterprise owner for a cross-asset Common Domain Model (CDM) supporting capital markets and investment banking. This role is responsible for defining and governing canonical business semantics for products, trades, lifecycle events, parties, agreements, reference data, and related domains to enable interoperability across front office, risk, finance, operations, regulatory reporting, and analytics platforms.

The role requires deep capital markets domain knowledge, strong data modeling discipline, and a governance-focused approach to schema versioning, lineage, and enterprise adoption.

Key Responsibilities

Enterprise CDM Ownership & Strategy

• Own the enterprise CDM vision, scope, and roadmap for capital markets domains across the full lifecycle
• Maintain domain decomposition and ensure consistent semantics across business lines and platforms
• Establish canonical modeling principles focused on interoperability and auditability

Canonical Modeling (Cross-Asset, Trade Lifecycle, Post-Trade)

• Design and maintain conceptual, logical, and canonical data models for:


• Products (rates, credit, FX, equities, securitized products)
• Trades, positions, lifecycle events, allocations, payments, and cashflows
• Parties, legal entities, accounts, agreements, settlement instructions, and reference data


• Normalize identifiers and hierarchies to support interoperability and reconciliation
• Develop modeling patterns for event-driven and state-based lifecycles

CDM Governance, Controls, and Operating Model

• Establish governance operating model for CDM in a regulated environment
• Enforce modeling standards, definitions, relationships, and metadata alignment
• Manage schema versioning and controlled release processes, including:


• Semantic versioning
• Backward compatibility and deprecation strategies
• Release documentation and impact analysis


• Maintain canonical-to-physical implementation patterns across platforms

Adoption Enablement Across the Enterprise

• Develop mapping templates and onboarding guidance for CDM adoption
• Create canonical transformation patterns and reference examples
• Partner with engineering and architecture teams to ensure consistent implementation
• Facilitate design reviews to maintain standardization

AI / LLM Integration

• Enable AI/ML and LLM use cases through:


• AI-ready canonical datasets
• Semantic layers and metadata structures
• Structured modeling from unstructured data sources


• Support governance requirements including reproducibility, explainability, and audit readiness

Required Experience

• 5+ years of data modeling experience within investment banking, broker-dealer, or capital markets environments
• Experience building or governing a canonical or enterprise Common Domain Model across multiple systems or business units
• Experience leading cross-functional stakeholder sessions across trading, risk, operations, finance, and data teams
• Experience defining canonical entities for:


• Trades, lifecycle events, valuations, and cashflows
• Parties, accounts, agreements, and reference data


• Experience driving enterprise adoption of canonical models, including mapping and onboarding systems
• Experience with data mapping and harmonization across trading and post-trade platforms
• Experience supporting risk and regulatory use cases with strong controls and governance focus

Preferred Qualifications

• Familiarity with ISDA CDM concepts and lifecycle modeling
• Experience aligning internal models to ISDA CDM and defining extensions
• Familiarity with FINOS ecosystem practices
• Experience integrating canonical models into:


• Event/streaming schemas
• Data warehouses/lakehouses
• API and message contract governance


• Exposure to AI/LLM enablement in regulated environments

Core Skills & Competencies

• Cross-asset canonical data modeling
• Data governance and auditability
• Versioning and change management
• Stakeholder alignment and decision-making
• Strong documentation and communication skills