Director, Data Architecture (AI/ML Foundations)

Palomar • La Jolla, CA

1d • Hybrid

About The Position

Palomar is hiring a Director, Data Architecture to design and build the connected data foundation that supports analytics, actuarial, data science, AI, and machine learning work. This is a new role responsible for setting the architecture, making key design decisions, and building the initial platform hands-on with a small team of AI data engineers. The role reports to the EVP, Head of AI, and works closely with Actuarial, Data & Analytics, Underwriting, Claims, and Finance.

The director will create a trusted, transaction-level record of the business from submission to policy to claim, with temporal history so figures can be traced to their sources and reproduced as of any date. The role leads data modeling, entity resolution, and the semantic layer to establish consistent identities for brokers, insureds, policies, locations, and claims. The foundation will make data usable by people, models, and AI agents through governed access, while meeting public-company standards for governance, reconciliation, and auditability.

The position owns the target architecture, data model, and roadmap for the AI/ML data foundation on Snowflake. It builds append-only temporal models, entity resolution and master data capabilities, and governed access to structured and unstructured data. It also develops feature pipelines, training datasets, retrieval, vector search, and governed tool access for AI and machine learning use cases. The director hires, leads, and develops a small engineering team and partners with Technology, Information Security, Legal, and Compliance on data protection, retention, and platform decisions.

The position is hybrid and requires working on-site three days per week in La Jolla, California. The listed pay range is $185,000–$250,000, with bonus potential and participation in the company’s long-term incentive program. Final compensation depends on factors including experience and qualifications.

Requirements

• Bachelor’s degree in Computer Science, Mathematics, Statistics, Engineering, Information Systems, or a related field, or equivalent practical experience.
• At least 10 years of experience in data engineering or data architecture.
• Personally designed and built an enterprise data model from raw sources to a conformed layer, such as dimensional, Data Vault, or temporal.
• Experience leading or mentoring engineers.
• Experience with entity resolution or master data at scale, including matching, golden records, and measured match quality.
• Production experience with Snowflake and dbt, strong SQL and Python, and engineering fundamentals including Git, automated testing, CI/CD, and infrastructure as code.
• Hands-on experience making data usable by AI and ML, including features, LLM-based document extraction, retrieval and vector search, semantic layers, and agent tool access such as MCP.
• Uses AI coding tools every day.
• Data experience in a SOX-audited or similarly regulated environment, including lineage, access control, and change management.
• Clear communication with actuaries, finance leaders, executives, and engineers, including the ability to explain tradeoffs and bring partners along.
• Ability to work on-site three days per week in a hybrid capacity.
• Demonstrable ability to work autonomously and drive progress.
• The posting emphasizes building relationships through transparency, trust, and respect; working resiliently and creatively in an agile environment; collaborating across diverse perspectives; acting with integrity; being innovative; and being intellectually curious, creative, and pragmatic.

Nice To Haves

• Property and casualty insurance or reinsurance data experience, especially specialty or excess and surplus, including policy, exposure, claims, bordereaux, or statistical reporting.
• Experience ingesting messy third-party data and writing specifications to improve data quality at the source.
• Experience with Snowflake ML (Feature Store, Model Registry), Cortex AI, or another production ML platform.
• SnowPro or dbt certification.
• Experience with semantic layers, ontologies, or knowledge graphs.
• Experience standing up a data function or platform from the ground up.
• Geospatial or catastrophe exposure data experience.

Responsibilities

• Own the target architecture, data model, and roadmap for the AI/ML data foundation on Snowflake.
• Design and build append-only, temporal transaction-level models that trace figures to source and support reproduction as of any date.
• Build entity resolution and master data across internal systems and external partners, measuring match quality and keeping merges traceable.
• Incorporate structured and unstructured data—including submissions, documents, bordereaux, loss runs, and third-party data—into a governed, queryable foundation, and define specifications for external data.
• Implement role-based access, separated environments, lineage, data-quality checks, and reconciliation in accordance with company governance and change-management standards.
• Maintain the data dictionary and metadata, with definitions shared across company reporting.
• Build feature pipelines, training datasets, retrieval, vector search, and governed tool access over the entity layer, using Snowflake ML and Cortex where appropriate.
• Partner with AI scientists and actuaries, owning features, retrieval, and lineage from source to feature to model.
• Measure foundation value using entity coverage, data quality, adoption, and the time required to answer new business questions.
• Hire, lead, and develop a small team of AI data engineers; set standards for testing, documentation, code review, data quality, and cost.
• Partner with Actuarial and Data & Analytics on architecture decisions, design reviews, standards, and shared definitions.
• Work with Technology, Information Security, Legal, and Compliance to ensure data is accessed, protected, and retained in line with company policies, and advise on what to build, buy, or retire.

Benefits

• Full suite of medical benefits.
• Long-term financial incentives, including stock.
• 401(k) with 3.5% automatic, fully vested employer contributions.
• Competitive paid time off and holiday program.
• Lifestyle spending allowance.
• Professional development assistance.
• Career exploration opportunities.
• Regular company-wide social events, including virtual events.
• Competitive annual discretionary bonus program and opportunity for annual long-term incentive stock grants.

What This Job Offers

• Job Type: Full-time
• Career Level: Director