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.

An in-person interview may be required during the hiring process

State specific pay scales for this role are as follows:

$118,614 to $230,619 (CA, NJ, NY, WA, HI, AK, MD, CT, RI, MA)

$107,876 to $209,653(NV, OR, AZ, CO, WY, TX, ND, MN, MO, IL, WI, FL, GA, MI, OH, VA, PA, DE, VT, NH, ME)

$97,089 to $188,688 (UT, ID, MT, NM, SD, NE, KS, OK, IA, AR, LA, MS, AL, TN, KY, IN, SC, NC, WV)

The expected base salary for this position will vary depending on a number of factors, including relevant experience, skills and location.

What You’ll Do

Metric Store & Semantic Modeling

· 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.

Analytics Engineering

· 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.

AI Persona & Prompt Engineering

· 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.

Cross-Functional Collaboration

· 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 We’re Looking For

· 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.

· 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.

Why choose a career at Mercury?

At Mercury, we have been guided by our purpose to help people reduce risk and overcome unexpected events for more than 60 years. We are one team with a common goal to help others. Everyone needs insurance and we can’t imagine a world without it.

Our team will encourage you to grow, make time to have fun, and work together to make great things happen. We embrace the strengths and values of each team member. We believe in having diverse perspectives where everyone is included, to serve customers from all walks of life.

We care about our people, and we mean it. We reward our talented professionals with a competitive salary, bonus potential, and a variety of benefits to help our team members reach their health, retirement, and professional goals.

Learn more about us here: https://www.mercuryinsurance.com/about/careers

Why Join Us

· Lead the transformation of our analytics ecosystem.

· Build foundational metric and AI capabilities used across the company.

· High visibility role with direct impact on business performance, distribution strategy, and operational efficiency.