Data Solution Architect (fin services)

Title: Data Solution Architect (fin services)
Location: New York, NY
Duration: 6+ months
Interviews: Technical, Project, Client

Job Description:
Initiative: The client envisions the RIPL platform as a groundbreaking, AI-driven investment ecosystem that revolutionizes the entire investment process by formulating an intuitive and human-centric design approach. This initiative transcends mere digitization, aiming to redefine investment decision-making with systematic, transparent, and intelligent solutions. Central to the client's strategy is crafting a platform that reflects Ray Dalio's investment philosophy while maintaining the versatility to cater to a wide array of users, e.g. from wealth funds to family offices. The advanced AI-native platform will be meticulously designed to meet the client's strategic needs, offering transformative capabilities for the investment landscape.
This project phase is to drive Elaboration for this greenfield initiative that will produce detailed MVP Roadmap, prioritized Backlog, Data/Application architecture and AI/Infrastructure blueprints as outcomes for the next MVP build phases. We are looking for a dynamic, hands-on Data Architect for this project who is going to be part of the core Program Team.

Responsibilities:

• Responsible for identifying and integrating structured, unstructured, and semi-structured data sources.
• This person will design role-based access control (RBAC) and develop logical data models, ensuring compliance and data lineage.
• This role involves documenting business transformations, establishing data quality approaches and rules,
• create a comprehensive data catalog.
• This architect registers data assets with metadata, focusing on sensitivity and security.
• This role designs the architectural blueprint for the Data Factory, encompassing acquisition, preparation, and consumption, ensuring robust data management and quality to support automated investment processes and AI-driven analytics.
• This person will be responsible for designing and implementing agents and agentic harness and reasoning harness.
• Graph RAG and Graph Data Layer
• Design and implement a Neo4j-powered Knowledge Graph as the central data layer for investment intelligence.
• Ensure investment decision traceability by linking research, strategies, and portfolio actions into a lineage graph.
• Develop and maintain a multi-dimensional asset ontology, enabling flexible categorization and cross-dimensional analysis.
• Architect adaptive schema evolution using AI-driven feedback loops and genetic algorithm principles.
• Integrate temporal versioning to support time-aware queries and historical context preservation.
• Enable thin-pointer architecture for scalable integration with large datasets without duplication.
• Incorporate GraphRAG for transforming unstructured documents into queryable graph entities with source attribution.
• Implement property-based access control for secure, multi-tenant data visibility and query-level protection.
• Oversee real-time data ingestion pipelines for structured, unstructured, and operational data sources.

Requirements:

• Snowflake
• Airflow
• Deep knowledge on Graph RAG and Graphs DS
• Data Architecture
• Experience working with various Market data sources
• Had experience in integrating with heavy AI driven and assisted architecture.
• Nice to have AWS skills
• Can teach and share knowledge with Client team on Cypher, Graph and RAG traversals.