Principal Data Platform Architect

Riskonnect• US,

About The Position

Riskonnect is building a unified enterprise data platform that will power reporting, advanced analytics, connected risk intelligence, and AI across a portfolio of market-leading SaaS products. This role offers the opportunity to shape the architecture, standards, and technical direction of a platform that will become foundational to the company's next generation of products. Riskonnect is seeking an experienced Principal Data Platform Architect to lead the technical architecture of our next-generation enterprise data platform. This leader will own the ongoing evolution of Riskonnect's enterprise data platform. Building on an established architectural foundation, the Principal Data Platform Architect will refine architecture, engineering standards, and implementation patterns as the platform expands across multiple SaaS products. This role will ensure the platform remains scalable, secure, performant, and ready to support advanced analytics, Connected Risk Intelligence, and future AI capabilities. Working closely with Engineering, Enterprise Architecture, Product Management, Data Engineering, and Analytics teams, this role will provide technical leadership for the ongoing evolution of Riskonnect's enterprise data platform. The Principal Data Platform Architect will drive architectural consistency across product teams, evolve shared platform capabilities and engineering standards, and help engineering organizations deliver trusted, secure, scalable, and AI-ready data solutions while preserving the flexibility required by individual SaaS products. This is a hands-on architecture leadership role. The Principal Data Platform Architect will guide architecture decisions, mentor engineering teams, evaluate emerging technologies, and partner closely with product engineering to ensure successful delivery of enterprise data capabilities. This role focuses on the architecture and evolution of Riskonnect's enterprise analytics, reporting, business intelligence, and AI data platform. While the platform ingests and transforms data from operational applications, the primary responsibility is defining the scalable data architecture, semantic models, governance, and engineering patterns that enable trusted analytics and AI across the Riskonnect portfolio. This role partners closely with product engineering teams but is not responsible for the design of transactional (OLTP) application architectures. Success in this role depends on enabling multiple autonomous engineering teams to deliver consistently through shared architecture, engineering standards, and technical leadership.

Requirements

12+ years designing enterprise data platforms.
5+ years leading cloud data architecture.
Deep expertise in dimensional data modeling and SQL.
Experience with scalable SaaS architectures, CDC technologies, and large-scale data pipelines.
Strong knowledge of cloud security, governance, and enterprise analytics platforms.
Ability to influence cross-functional engineering teams without direct authority.
Excellent communication skills with both technical and executive audiences.

Nice To Haves

Microsoft Fabric
OneLake
Power BI
Azure Data Services
Informatica
Salesforce
SQL Server
MySQL
Oracle
Azure DevOps
GitHub

Responsibilities

Own the enterprise data platform architecture and long-term technical direction.
Evolve and maintain enterprise standards for data ingestion, storage, transformation, semantic modeling, governance, security, and analytics.
Refine and expand reusable architecture patterns and reference implementations across multiple SaaS product teams.
Partner with Enterprise Architecture on roadmap and technology strategy.
Lead architecture for Microsoft Fabric, OneLake, Lakehouse architecture, Bronze/Silver/Gold models, semantic models, Power BI, and AI-ready data services.
Establish architectural guidance for CDC, streaming, ELT, metadata, lineage, data quality, governance, and lifecycle management.
Lead enterprise logical and physical data modeling, including Star and Snowflake schemas.
Design scalable multi-tenant architectures supporting customer-specific schemas, custom fields, identity federation, Row-Level Security, and tenant isolation.
Drive architectural governance by reviewing major solution designs, ensuring adherence to enterprise standards, and balancing consistency with product team autonomy.
Partner across Product Engineering, Product Management, DevOps, Security, Analytics, and Customer Success.
Ensure the platform enables future AI capabilities including RAG, semantic search, vector-ready architectures, and AI-ready datasets.