Senior Data Modeler (contract)

In this contingent resource assignment, you may: Consult as an expert to develop or influence initiatives and resources for highly complex business and technical needs across Engineering. Consult on the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, and advanced analytical and inductive thinking. Provide expertise to client senior leadership on innovative Engineering business solutions. Strategically engage with client personnel. Required Qualifications: Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education., Wells Fargo is 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-enabling interoperability across front office, risk, finance, operations, regulatory reporting, and analytics platforms., 1) Enterprise CDM Ownership & Strategy

• Own the enterprise CDM vision, scope, and roadmap for capital markets domains (cross-asset; end-to-end lifecycle).
• Maintain a clear domain decomposition (bounded contexts) and ensure consistent semantics across lines of business and platforms.
• Establish model "north star" principles: canonical semantics first, implementation-agnostic logical model, interoperability, and auditability.

2. Canonical Modeling (Cross Asset, Trade Lifecycle, Post Trade)

• Design and maintain conceptual/logical/canonical models for:

o Products (rates, credit, FX, equities, securitized products as applicable) o Trades & positions, events/lifecycle states, allocations, payments/cashflows o Parties & legal entities, accounts, agreements/CSA, settlement instructions, reference data

• Normalize identifiers and hierarchies (trade IDs, UTI/USI considerations where applicable, party identifiers, instrument identifiers) to support interoperability and reconciliation.
• Provide model patterns for event-driven and state-based lifecycles to support downstream processing consistency.

3. CDM Governance, Controls, and Operating Model

• Establish operating model for CDM governance in a regulated environment (e.g., design authority participation, steward/owner workflows, approvals, audit-ready documentation).

o Enforced modeling standards (naming, definitions, relationships, cardinality, constraints) o Lineage/metadata completeness (dictionary, glossary alignment, stewardship mapping)

• Manage schema/model versioning and controlled release processes for a shared enterprise model:

o semantic versioning o backward compatibility/deprecation strategy o release notes and consumer migration guidance o impact analysis for breaking changes

• Maintain canonical-to-physical implementation patterns (e.g., lakehouse tables, event schemas, API contracts) without conflating the logical CDM with any single platform.

6. Adoption Enablement Across the Enterprise

• Drive adoption by producing and maintaining:

o Mapping templates and guidance for onboarding systems to the CDM o Canonical transformation patterns (ingest standardize validate publish) o Reference examples (sample payloads, canonical entities, event examples)

• Partner with engineering, architecture, and platform teams to ensure the CDM is implementable and consistently consumed.
• Facilitate design reviews to prevent proliferation of conflicting definitions and "shadow models."

7. AI / LLM Integration (Enterprise Enablement)

• Ensure the CDM supports AI/ML and LLM use cases by:

o Designing AI-ready canonical datasets (analysis-grade views, curated canonical training sets) o Enabling semantic layers for RAG/knowledge retrieval (controlled vocabularies, taxonomies, metadata enrichment) o Supporting unstructured-to-structured modeling patterns (e.g., confirmations/agreements extracted terms canonical fields)

• Collaborate with AI governance / model risk partners to ensure CDM usage supports:

o Reproducibility (versioned training datasets tied to CDM releases) o Explainability inputs (clear definitions and lineage) o Audit-ready documentation of semantic decisions

The successful candidate will combine deep capital markets domain knowledge with strong modeling discipline and a control-minded approach to governance, schema versioning, lineage, and adoption. Experience aligning enterprise models to ISDA CDM and leveraging the FINOS ecosystem (standards practices, model sharing patterns, and open collaboration approaches) is highly valued., * Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship.

• Hands-on data modeling experience within an investment bank, broker-dealer, or capital markets technology organization, supporting front-to-back workflows (Front Office / Risk / Operations / Finance / Regulatory).
• Demonstrated experience building, governing, or materially contributing to a canonical / enterprise Common Domain Model (CDM) (or equivalent canonical model) used across multiple systems, lines of business, or platforms in a capital markets environment.
• Proven ability to lead working sessions with stakeholders across Trading, Risk, Operations, Finance, Regulatory Reporting, Architecture, and Data Engineering to drive consensus on canonical semantics and resolve competing definitions.
• Experience defining canonical entities and relationships for core capital markets domains, such as:

o Trades, positions, lifecycle events, valuations, and cashflows/payments o Parties/legal entities, accounts/books, agreements/CSAs, and reference data

• Demonstrated experience delivering enterprise adoption of a canonical model:

o creating mappings from source systems to canonical entities o onboarding multiple producer/consumer systems o resolving semantic conflicts and driving standardized definitions across stakeholders

• Direct experience performing data element mapping and harmonization across heterogeneous trading and post-trade platforms (vendor + proprietary), including lineage and reconciliation requirements typical of investment banks.
• Experience supporting risk and regulatory use cases that rely on consistent canonical semantics (e.g., exposure aggregation, sensitivities, trade reporting, risk controls, finance substantiation), including evidence of controls-minded modeling.

Preferred Qualifications (Strengthened for ISDA/FINOS SME)

• Hands-on familiarity with ISDA CDM concepts and lifecycle representation patterns
• Experience performing alignment mapping from internal models to ISDA CDM and defining extensions
• Familiarity with FINOS ecosystem practices relevant to domain models (interoperability patterns, documentation approaches, reference implementations/tooling patterns)
• Experience integrating canonical models into:

o streaming/event schemas (e.g., lifecycle event payloads) o lakehouse/warehouse physical models o API and message contract governance

• Exposure to AI/LLM enablement patterns (RAG-ready metadata, semantic layers, curated training datasets) in regulated environments