Lead Data Platform Architect

Responsibilities

• Owns architecture direction across the major capabilities of the enterprise data platform, including ingestion, storage, distributed processing, data warehouse, integration, metadata, semantic layers, lineage, observability, security, and resilience.
• Develops and maintains the platform target-state architecture and transition roadmap, driving toward a unified, consolidated view of business subject areas such as policies, claims, billing, rating, general ledger, and annuities.
• Personally designs and resolves the most complex and highest-risk platform architecture problems, including cross-component data flows, platform consolidation, new data-asset ingestion, partner onboarding, and data conversions into new administrative systems.
• Defines reusable reference designs, architecture patterns, guardrails, and nonfunctional requirements for scalability, performance, resilience, security, operability, and cost effectiveness that engineering teams apply.
• Designs AI-ready data foundations and establishes architecture standards for data quality, lineage, and observability that keep model training and inference data accurate, reproducible, and auditable.
• Leads data profiling and conceptual, logical, dimensional, and physical modeling for complex subject areas and sets modeling standards for the platform.
• Evaluates emerging platform and AI capabilities, such as vector databases, semantic layers, and LLM-based tooling, through architecture assessment or proof of concept and recommends adoption approaches.
• Leads technical design sessions and architecture reviews; reviews high-impact engineering designs and code for alignment with architecture standards and establishes design and coding practices that are maintainable and supportable.
• Partners with Platform Engineering & Operations and Data Engineering on capacity, performance, batch run-time, and cloud-cost concerns by identifying architectural causes and defining architectural improvements and refactoring approaches.
• Provides architecture leadership for severe or recurring incidents and major defects with architectural causes, including root-cause analysis and remediation plans, and coordinates resolution with engineering and operations teams.
• Partners with data governance, security, compliance, and audit teams to ensure platform architecture supports enterprise governance frameworks, security standards, AI-related data use, and financial-reporting controls such as SOX.
• Serves as architecture point of contact for business stakeholders and IT partners, including application owners, integration teams, and vendors, on platform capabilities and data-exchange interfaces.