Overview:
Role Name - Lead Data Modeler
Malvern, PA
Demonstrated expertise in conceptual, logical, canonical, semantic, and physical data modeling.
Deep understanding of enterprise information architecture and metadata management.
Experience developing business-oriented canonical models independent of application implementations.
Strong understanding of business rule modeling, cardinality, optionality, integrity constraints, and relationship semantics.
Expertise in enterprise modeling patterns such as Party, Role, Agreement, and Classification.
Strong understanding of Supertype / subtype modeling, Temporal modeling. Associative entities, Reference data design, and Master data concepts • Experience supporting analytics, regulatory reporting, operational data quality, and AI-enabled business use cases through enterprise data modeling.
Experience establishing or contributing to enterprise data modeling, governance and stewardship functions.
Experience with enterprise data modeling tools such as ERwin, ER Studio, and maintaining enterprise data dictionaries.
Ability to create reusable business concepts and canonical models that support long-term information architecture strategy.
Roles & Responsibilities
Partner with business data stewards and product teams to define and evolve business concepts, entities, relationships, and business rules.
Own the holistic Personal Wealth logical and canonical data model and maintain traceability to implementation assets.
Lead development of canonical models supporting householding, advisor teaming, client relationships, investment offerings, and operational workflows.
Support strategic initiatives such as Portfolio of the Future by designing canonical models and abstraction layers that isolate Client business concepts from vendor-specific schemas.
Define standards and best practices for conceptual, logical, physical, canonical, and semantic data modeling.
Establish governance processes supporting model stewardship, versioning, lifecycle management, and change control.
Partner with Enterprise Data Architecture and Engineering teams to implement tooling supporting model management, metadata management, lineage, and governance.
Collaborate with integration teams to design Anti-Corruption Layer (ACL) patterns and mapping frameworks between vendor platforms and Client canonical data models.
Facilitate workshops to identify, define, and validate enterprise business concepts and relationships.
Mentor architects, analysts, and engineers in modern data modeling practices.
Support data models used across advice delivery, wealth management, client servicing, analytics, regulatory reporting, and AI-enabled experiences. • Drive adoption of enterprise modeling standards and reusable business concepts across product and engineering teams.
Establish and promote common business language and shared enterprise concepts across Personal Wealth platforms.
Ensure canonical models provide a stable abstraction layer between business domains, internal systems, and vendor platforms.
Skills: Digital : Python~Digital : Amazon Web Service(AWS) Cloud Computing~Digital : Collibra~Domain : US Capital Markets Experience Required: 10 & Above
Email me for prompt response.
Skills:
LIFECYCLE MANAGEMENT,DATA MODELING,METADATA MANAGEMENT
