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Data Solution Architect

EPAM SystemsNew York, NY🇺🇸United StatesPosted 5 Jul 2026

Why This Role Stands Out

You'll architect a sophisticated, AI-driven financial platform, driving innovation in a high-impact role with significant growth potential. This hybrid opportunity is perfect for a seasoned Data Solution Architect with expertise in graph databases, AI, and cloud platforms, eager to shape the future of financial technology.

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Join a cutting-edge multi-service platform for financial analysis, portfolio construction, and AI-assisted investment advisory. The platform integrates a Snowflake-backed data lake, dual-graph knowledge architecture (Neo4j), and a governed LLM advisor, all exposed via streaming chat and voice. The stack includes a React/TypeScript frontend and FastAPI backend, orchestrated with modern DevOps and governance practices. Req# Responsibilities Own end-to-end architecture from data assets to AI-driven user experience, ensuring coherent contracts and verifiable paths across all layers Design, implement and maintain dual-graph knowledge systems, financial DSLs and agent orchestration gateways Author and steward ADRs/RFCs for robust governance and traceability for all architectural decisions Integrate cloud data platforms (Snowflake, AWS EKS) and enforce security, compliance and auditability standards Deliver features iteratively with high test coverage and clear documentation for engineering and compliance stakeholders Requirements Hands-on experience with Python (FastAPI, asyncio, pytest), monorepo discipline and data system design Deep expertise in data architecture: ontology, taxonomy, modeling and data contracts Proficiency in Neo4j knowledge graph design, Cypher and GraphRAG patterns Experience with design and implementation of domain-specific languages (DSLs) and YAML/DSL pipelines Strong background in AI agent orchestration, responsible AI governance and cloud integration (Snowflake, AWS, Helm, ArgoCD) Nice to have Experience with productization of AI advisors for regulated finance, including compliance demos, audit chains and human-in-the-loop design Familiarity with formal methods (Alloy, TLA+), advanced modeling languages (RDF/SHACL, SKOS) and voice/multimodal AI integration Proven track record in migration of prototypes to production, deprecation of legacy systems and architecture governance for multi-service platforms Strong skills in observability (OTEL, Grafana), CI/CD automation and authorship of scalable agent skills or process automation Expertise in compliance frameworks, regulatory traceability and advanced information architecture for documentation

Skills

FastAPI
Neo4j
AWS
Snowflake
ArgoCD
Grafana
Helm
LLM
Python
React
TypeScript
pytest

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