> Markdown version of [/jobs/ext/239860-data-analytics-engineer-ii](https://www.wearedevelopers.com/jobs/ext/239860-data-analytics-engineer-ii). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Analytics Engineer II

- **Company:** Mercury Insurance Services, LLC
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $77,283.0 - $179,048.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Business Analytics Applications, Data Analysis, BigQuery, Software Debugging, Django Web Framework, Jinja (Template Engine), Python (Programming Language), YAML, Macros, Sql Optimization, Flask (Web Framework), Snowflake, Prompt Engineering, Fastapi, Pandas, Information Technology, Data Lineage, Data Analytics, Api Design
- **Published:** May 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ba12e07905b7df00

## About the Role

* 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

## Description

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), * 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


## Related Videos

- [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail)
- [CI/CD with Github Actions](https://www.wearedevelopers.com/videos/856-ci-cd-with-github-actions)
- [Crafting Custom Frameworks with Rust: A Deep Dive into Procedural Macros](https://www.wearedevelopers.com/videos/849-crafting-custom-frameworks-with-rust-a-deep-dive-into-procedural-macros)
- [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript)
- [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data)
- [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt)

## Related Articles

- [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)
- [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk)
- [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)
- [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)
- [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)
- [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)