Lead Analytics Engineer – Metrics & AI Enablement

Mercury Insurance Services, LLC

2d

About The Position

We’re looking for a Lead Analytics Engineer to build our next-generation enterprise metrics store and enable insights across underwriting, sales, product, claim and experience. This role blends analytics engineering and prompt engineering, supporting our journey toward a fully governed, AI-ready data ecosystem.
You will define how metrics are created, governed, and consumed—and design prompts and behaviors for internal AI personas that deliver trusted insights to business teams.

Requirements

• 7+ years in analytics engineering, data engineering, or BI engineering.
• BS in STEM major is required. MS is preferred.
• Expert SQL and strong hands-on experience with dbt (semantic layer, macros, tests).
• Deep understanding of data modeling and governed metric design.
• Experience building a metric layer, metrics store, or semantic model in production.
• Practical experience with LLMs or prompt engineering for AI assistants.
• Strong communication skills and ability to partner with business stakeholders.

Nice To Haves

• Experience in P&C insurance data (Quote, Bind, Policy, Claims, Agent) is a plus.
• Familiarity with LLM retrieval, embeddings, or knowledge bases is a plus.
• Experience with Airflow, Dagster, Prefect, or dbt Cloud is a plus.

Responsibilities

• Build and maintain our enterprise metrics store (Tier 1–3 KPIs).
• Define metric relationships, hierarchies, lineage, and semantic layers using dbt.
• Partner with engineering and business teams to unify metric logic and governance.
• Implement automated data quality checks and testing.
• Develop high-quality dbt models, reusable marts, and production-grade SQL.
• Optimize performance in cloud data warehouses (Snowflake/BigQuery/Redshift).
• Support dashboards, API consumers and operational systems.
• Maintain documentation, standards, and CI/CD for analytics workflows.
• Design prompts, logic flows, and knowledge structures for LLM-powered internal agents.
• Create metric-aware AI interactions that provide accurate, governed insights.
• Reduce hallucination risk through prompt patterns, guardrails, and validation steps.
• Collaborate with product and business teams to define AI personas for key roles.
• Work closely with underwriting, sales, product, claim and experience analytics team
• Translate business logic into certified metrics and scalable models.
• Mentor junior analytics engineers and contribute to internal best practices.

What This Job Offers

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