Data Modeler/Architect
New York, NY, United States
Full Time Senior-level / Expert USD 122K - 215K
BNY
BNY is a global financial services company overseeing nearly $50 trillion — managing it, moving it and keeping it safe.Our Team
Data Solutions and Services is focused on delivering the firm’s master data strategy, implementing enterprise data policies & governance, driving a holistic access to data via our data Lake, and enabling the business to deliver advanced outcomes for ourselves and our customers using AI/ML techniques.
In the process of focusing on this agenda - we participate in the remediation of data centric regulation. We help our operations teams transform how we operate, while optimizing our data centric cost structure and reducing our operating & regulatory risk, and provide innovative, data centric commercial opportunities.
The Role
We are seeking a skilled Data Modeler/ Architect with a strong background in financial services, specifically securities services, to lead the development and implementation of taxonomies and ontologies aligned with the Financial Industry Business Ontology (FIBO) standards. This role combines expertise in ontology development, financial domain knowledge, and data architecture to create and manage a centralized knowledge framework that enhances data integration, decision-making, and regulatory compliance across the organization.
Ontology Development
• Design and develop ontologies and taxonomies for securities services, incorporating industry standards such as FIBO, ISO 20022, and SWIFT.
• Model financial concepts, relationships, and processes within securities services (e.g., settlement, custody, corporate actions).
• Use semantic technologies (e.g. OWL) and ontology tools (e.g., Protégé, WebProtégé) to implement the ontology.
• Ensure consistency and alignment with enterprise data models and business workflows.
Data Architecture
• Design and maintain data architecture for storing, integrating, and querying ontology-driven data in ERwin
• Build and implement knowledge graphs or semantic models to support advanced querying and reporting needs.
• Define data pipelines to integrate external data sources (e.g., custodians, depositories) with the ontology framework.
• Collaborate with IT and data engineering teams to ensure scalability and system performance.
Financial Domain Expertise
• Act as a subject matter expert on securities services, providing insights on trade lifecycles, settlement, custody, and regulatory requirements.
• Work with internal stakeholders (e.g., portfolio managers, risk teams, compliance teams) to ensure ontologies reflect real-world operations and meet business requirements.
• Stay updated on evolving industry standards and regulatory frameworks impacting securities services.
Collaboration and Governance
• Partner with data governance teams to ensure taxonomy and ontology adherence to data quality and security standards.
• Collaborate with cross-functional teams (front, middle, and back office) to identify and prioritize use cases for the ontology.
• Conduct workshops and training sessions to promote ontology adoption and educate teams on semantic technologies.
Required Skills and Qualifications
Technical Expertise
• Proficiency in data modeling tools such as ERwin.
• Strong knowledge of semantic technologies (RDF, OWL, SPARQL) and knowledge graph platforms (e.g., Neo4j, GraphDB, Stardog).
• Experience in data architecture, including data modeling, database design, and integration (e.g., relational and graph databases).
• Familiarity with FIBO standards and their application in securities services.
Financial Domain Knowledge
• Strong understanding of securities services, including settlement, custody, corporate actions, and cash management.
• Familiarity with financial products such as equities, bonds, derivatives, and investment funds.
• Knowledge of industry standards such as SWIFT, ISO 20022, and regulatory frameworks (e.g., MiFID II, SFTR).
Other Skills
• Analytical and problem-solving skills with the ability to abstract complex financial processes into models.
• Strong communication skills to liaise with technical teams, business users, and external stakeholders.
• Self-motivated with the ability to lead projects and work independently in a fast-paced environment.
Preferred Qualifications
• Master’s or PhD in Computer Science, Data Science, Finance, or a related field.
• Experience in developing and managing knowledge graphs or enterprise ontologies.
• Certifications in data management (e.g., DAMA), FIBO, or semantic technologies.BNY is an Equal Employment Opportunity/Affirmative Action Employer. Minorities/Females/Individuals with Disabilities/Protected Veterans. Our ambition is to build the best global team – one that is representative and inclusive of the diverse talent, clients and communities we work with and serve – and to empower our team to do their best work. We support wellbeing and a balanced life, and offer a range of family-friendly, inclusive employment policies and employee forums.
Our Benefits and Rewards:
BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time that can support you and your family through moments that matter.
BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans
BNY assesses market data to ensure a competitive compensation package for our employees. The base salary for this position is expected to be between $122,000 and $215,000 per year at the commencement of employment. However, base salary if hired will be determined on an individualized basis, including as to experience and market location, and is only part of the BNY total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, short and long-term incentive packages, and Company-sponsored benefit programs.
This position is at-will and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation) at any time, including for reasons related to individual performance, change in geographic location, Company or individual department/team performance, and market factors.
Tags: Architecture Computer Science Data governance Data management Data pipelines Data quality Data strategy Engineering Finance Machine Learning Neo4j PhD Pipelines RDF Security Swift
Perks/benefits: Competitive pay Health care
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