Principal Data & AI Architect

The Hartford · Hartford · $140,000–$210,000 (stated in the posting)

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Dir Data Architecture - GT06AE

We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.   

As a Principal Data & AI Architect, you will be a strategic technical leader responsible for defining and advancing data architecture that makes enterprise data trusted, connected, reusable, and ready for analytics, machine learning, Generative AI, and agentic applications. You will develop line-of-business and cross-domain architectures spanning data products, semantic layers, cloud data platforms, open lakehouse technologies, metadata, integration, and AI-ready data access. You will work in a multi-cloud environment where Snowflake on AWS is the primary enterprise data platform and Google Cloud provides strategic AI, machine learning, agent, and advanced analytics capabilities.


As a senior individual contributor, you will influence enterprise technology decisions, establish reusable architecture patterns, guide complex initiatives, and mentor architects and engineers across the organization. You will also work hands-on with emerging technologies to rapidly experiment, build prototypes, and demonstrate the art of the possible for new data and AI capabilities.


This role will have a hybrid work arrangement with 3 days a week in office in any of the following locations: Charlotte, NC; Hartford, CT; Columbus, OH or Chicago, IL.  Candidates must be eligible to work in the US without company sponsorship.


Primary Job Responsibilities


Strategic Data Architecture Leadership: Define line-of-business and cross-domain data architectures aligned with enterprise data, AI, cloud, and technology strategies. Translate business needs into target-state architectures, roadmaps, standards, and reusable patterns.

AI-Ready Data Architecture: Design governed data foundations that make structured, semi-structured, and unstructured data discoverable, understandable, accessible, and fit for analytics, machine learning, Generative AI, retrieval-augmented generation, and agentic solutions.

Semantic Layer Architecture: Define and evolve semantic models, governed metrics, business vocabularies, ontologies, and knowledge graphs that provide consistent business meaning across analytics and AI. Establish guidance for semantic governance, lifecycle management, interoperability, lineage, provenance, and access control.

Agentic Analytics: Architect the data and semantic capabilities required for conversational and agentic analytics, including natural-language data access, proactive insight generation, anomaly analysis, root-cause analysis, and decision support. Define controls for grounding, query validation, traceability, observability, evaluation, and human review.

Multi-Cloud Data Architecture: Establish secure and cost-effective patterns for integrating Snowflake on AWS with Google Cloud AI and analytics services using selective replication, federation, APIs, streaming, caching, open table formats, or other approved access methods.

Apache Iceberg and Open Lakehouse: Define standards and adoption guidance for Apache Iceberg, object storage, open catalogs, table lifecycle management, and multi-engine interoperability across Snowflake, AWS, Google Cloud, Spark, and related technologies.

Data Product and Integration Architecture: Define architecture for governed data products, including domain boundaries, data contracts, canonical entities, quality expectations, metadata, lineage, access interfaces, service levels, and lifecycle ownership. Guide batch, streaming, event-driven, API, change-data-capture, and federated integration patterns.

Governance, Security, Privacy, and Responsible AI: Embed data quality, metadata, lineage, security, privacy, retention, regulatory compliance, provenance, and responsible AI requirements into architecture designs. Ensure AI-enabled solutions support traceability, explainability, reliability, auditability, and appropriate human oversight.

Technology Leadership and Influence: Lead architecture reviews, assess emerging technologies, and perform focused hands-on experiments and rapid prototyping to validate concepts, evaluate feasibility, and demonstrate the art of the possible. Document architecture decisions and create standards, reference architectures, decision trees, and implementation patterns. Influence senior stakeholders and drive adoption across architecture, engineering, analytics, data science, product, governance, privacy, and cybersecurity teams.

Mentorship and Community Leadership: Mentor architects and engineers, elevate technical practices, and contribute to architecture forums and communities of practice. Communicate complex architecture choices in terms of business value, risk, interoperability, reliability, and cost.


Skills


Required Experience


Preferred Qualifications

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

$140,000 - $210,000

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

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