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Data Analytics Engineer II

Mercury Insurance Services, LLC -
Remote

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Job Details

$77,283 - $179,048 a year

Benefits

Paid holidays
Health insurance
Dental insurance
Paid time off
Vision insurance
401(k) matching
Referral program
Pet insurance

Qualifications

Data model design
SQL
Pandas
Bachelor's degree
YAML
Project stakeholder communication
Data analytics technologies
Database software proficiency

Full Job Description

Overview:

Position Summary:

We’re looking for an Analytics Engineer II 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.
As an Analytics Engineer, you will sit at the intersection of:

data modeling (dbt, semantic layer)
business metrics (insurance domain: quotes, binds, premium, agency performance)
analytics engineering (root cause analysis, metric relationships, metric store)

This is a hands-on role where you will design, build, and scale core metrics and analytical workflows, working closely with product, business, and engineering stakeholders. The team is evolving toward exposing metric infrastructure as internal services, so you’ll have the opportunity to shape that API layer as it matures.

Geo-Salary Information:

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

State specific pay scales for this role are as follows:

$94,458 to $179,048 (CA, NJ, NY, WA, HI, AK, MD, CT, RI, MA)

$X85,871 to $162,771 (NV, OR, AZ, CO, WY, TX, ND, MN, MO, IL, WI, FL, GA, MI, OH, VA, PA, DE, VT, NH, ME)

$77,283 to $146,494 (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.

Responsibilities:

Essential Job Functions:

Build and scale the metric layer
Develop and maintain dbt models
Contribute to semantic layer definitions (metrics, dimensions, relationships)
Ensure consistency and correctness of: key business metrics o metric hierarchies (metric pyramid)
Implement analytical logic (root cause analysis & metric insights)
Build root cause analysis workflows:
Implement baseline comparisons , companion metric analysis
Translate business questions into scalable analytical patterns
Enable metric consumption across tools
Support metric usage in different BI or analytical tools
Build reusable logic that avoids duplication across tools
Prepare for future API-based metric serving layer
Partner with business and product stakeholders
Work closely with sales, product, underwriting, claims, experience and other business teams, Translate ambiguous questions into:
Structured metrics
Actionable insights
Improve data quality and governance
Define and enforce:
Metric definitions
Dimension standards
Data contracts
Debug issues across:
Upstream pipelines
Semantic layer
Analytical outputs

Qualifications:

Education:

Bachelor's Degree in Computer science, Statistics or similar
3–5 years of analytics engineering or similar analytical role experience with dbt or similar transformation frameworks proficiency: models, tests, incremental materialization, Jinja macros
Advanced SQL on a columnar warehouse (Redshift, Snowflake, or BigQuery)
Python for data transformation and analysis (pandas, basic scripting)
Comfort working with YAML-based configuration and version-controlled analytics workflows
Clear written and verbal communication—able to explain metric definitions and data lineage to non-technical stakeholders
Nice to have
P&C insurance domain experience
Experience with:
Cohort analysis
Funnel metrics
Performance analysis
Familiarity with MetricFlow specifically and the dbt Semantic Layer
Exposure to Retool or similar low-code tools for operational write-back workflows
FastAPI or similar Python API frameworks (Flask, Django REST) for serving data products as services

About the Company:

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

Perks and Benefits:

We offer many great benefits, including:

Competitive compensation
Flexibility to work from anywhere in the United States for most positions
Paid time off (vacation time, sick time, 9 paid Company holidays, volunteer hours)
Incentive bonus programs (potential for holiday bonus, referral bonus, and performance-based bonus)
Medical, dental, vision, life, and pet insurance
401 (k) retirement savings plan with company match
Engaging work environment
Promotional opportunities
Education assistance
Professional and personal development opportunities
Company recognition program
Health and wellbeing resources, including free mental wellbeing therapy/coaching sessions, child and eldercare resources, and more

Mercury Insurance is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by federal, state, or local law.

Pay Range: USD $94,458.00 - USD $179,048.00 /Yr.

Apply Now

Refine Your Search

analytics statistics engineer jobs

Data Analytics Engineer II

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Enterprise Database Engineer

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