This Principal Solution Architect, Data role will have a strong focus on data solution architecture, modern data platforms, data products, and AI-enabled capabilities across the Insurance business.
The role bridges business, engineering, architecture, and data teams to rapidly design, build, and deploy scalable solutions that improve underwriting, enrollment, billing, claims, customer service, Producer, reporting, analytics, and digital experiences.
The architect will champion a data product mindset, treating data as a strategic enterprise asset with clear ownership, quality standards, reusable capabilities, governance, and measurable customer value.
Key Responsibilities:
Own and shape enterprise or business solution architecture strategy, standards, and patterns across multiple platforms and domains.
Define and maintain reference architectures and reusable design patterns (“golden paths”) for solution delivery.
Establish architectural guardrails that enable scalable, secure, and consistent solution design across teams.
Own reusable solution patterns, reference architectures, golden paths, and cross-team design consistency.
Work with Solution Architects to drive adoption; Head of Portfolio Architecture to tailor for BU context; Principal Enterprise Architect to align with enterprise standards.
Lead enterprise-level or business-level design decisions for complex, high-impact initiatives that span multiple value streams or business units.
Provide architectural oversight and guidance across portfolios, ensuring alignment to enterprise standards and long-term strategy.
Drive early engagement on initiatives to identify cross-platform dependencies, systemic risks, and scalability constraints.
Partner with Enterprise Architecture and platform teams to define build vs. buy guidance and integration patterns.
Translate business and technology strategy into actionable architecture direction and solution designs.
Partner with Security, Risk, and Compliance teams to embed governance, security, and regulatory requirements into solution architecture.
Define and promote best practices for operational resilience, scalability, performance, and maintainability.
Escalate enterprise exceptions, non-standard patterns, and enterprise-risk decisions.
Influence and align stakeholders across engineering, product, and business leadership without direct authority.
Mentor and coach architects and senior engineers to elevate architectural maturity across the organization.
Represent solution architecture in enterprise forums, architecture review boards, and strategic technology discussions.
Influence Value Stream leaders, Product Managers, Product Owners, and Tech Leads to align roadmaps, MVP scope, and technical trade-offs.
Where applicable, the role will be accountable to build solutions that scale and algin to business and technology requirements.
Be available for production incidents with major impact to business operations.
Understand and participate across portfolio initiatives, connect dependencies and opportunities across programs to optimize solutions, increase reuse, and reduce data waste.
Drive the adoption of a data product operating model across the organization.
Champion data product thinking by promoting customer-centric design, product ownership, continuous improvement, and measurable business value.
Establish best practices for discoverability, usability, interoperability, governance, and consumption of enterprise data products.
Translate business strategy into scalable technology, data, and analytics solutions.
Lead discovery workshops and data solution design sessions across underwriting, enrollment, billing, claims, customer service, reporting, and digital channels.
Influence enterprise technology strategy by identifying reusable capabilities and modernization opportunities.
Develop reusable frameworks, accelerators, and reference architectures to improve data delivery speed, consistency, and reuse.
Design modern data platforms and pipelines that support real-time and batch processing, scalable data integration, and enterprise analytics needs.
Ensure high-quality, trusted data through governance, observability, lineage, metadata, and automated data quality controls.
Collaborate with data engineering, product, and AI teams to operationalize AI-enabled data solutions within the data ecosystem.
Foster collaboration across architecture, engineering, product management, security, data, AI, and business teams.
You Have (Required Skills):
Deep experience designing and governing enterprise-scale solution architectures across multiple teams and domains.
Proven ability to define and drive adoption of architecture standards, frameworks, and reusable patterns.
Strong understanding of modern technology ecosystems, including application architectures, APIs and delivery, integration patterns, AI, cloud platforms, and data flows.
Experience balancing business priorities, technical trade-offs, and risk at an enterprise level.
Demonstrated ability to operate at both strategic and hands-on levels when needed.
Strong experience influencing technical direction across distributed teams without direct reporting authority.
Ability to bridge business and technology, translating strategy into clear architectural direction.
Excellent communication skills with the ability to convey complex concepts to both technical and non-technical audiences.
Experience working in regulated or risk-sensitive environments with strong awareness of governance and compliance needs.
Track record of mentoring architects and engineers and elevating organizational capabilities.
Experience collaborating within Agile / product-based delivery models.
Experience producing product-level and team-level technical design documentation.
Additional Required Data-Focused Qualifications:
Bachelor’s or master’s degree in computer science, Engineering, Information Systems, or a related field.
15+ years of experience in data integration, data architecture, data modeling, data engineering, solution architecture, or enterprise technology.
Proven experience designing and delivering enterprise-scale data platforms, data products, or analytics capabilities.
Strong understanding of modern data architecture principles, including data mesh, data products, metadata, governance, and domain-driven design.
Experience with modern data platforms such as Databricks, Apache Spark, Delta Lake, Kafka, or similar technologies.
Experience rolling out AI capabilities or AI-enabled solutions within a data ecosystem.
Experience within insurance industry, including enrollment, eligibility, policy administration, billing, claims, customer data, and employer administration.
Expertise in cloud platforms such as AWS, Azure, or Google Cloud Platform, APIs, microservices, and distributed systems.
Strong programming and data engineering skills in Python, PySpark, and SQL.
Exceptional communication, executive presence, and stakeholder management skills.
Experience leading data product initiatives, including proof-of-concept development and feasibility assessment.
Familiarity with product management methodologies and Agile frameworks.
Success Measures:
Increased adoption and reuse of enterprise data products.
Improved business outcomes through product-driven data capabilities.
Faster delivery of business initiatives through reusable platforms and engineering accelerators.
Increased adoption of AI-powered solutions across organization.
Higher data quality, trust, discoverability, and governance.
Strong cross-functional alignment between business, product, engineering, architecture, and data organizations.
Establishment of a sustainable product culture that treats data as a strategic enterprise asset.
