Data Analytics Engineer II
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Job Description
Analytics Engineer II role at Mercury Insurance focusing on building a metrics store and insights across business domains. Collaborate with product and engineering to enhance the analytics infrastructure.
Responsibilities:
- 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 and 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
- Improve data quality and governance
- Define and enforce metric definitions, dimension standards, data contracts
- Debug issues across upstream pipelines, semantic layer, analytical outputs
Requirements:
- 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
- P&C insurance domain experience (nice to have)
- Experience with Cohort analysis, Funnel metrics, Performance analysis (nice to have)
- Familiarity with MetricFlow specifically and the dbt Semantic Layer (nice to have)
- Exposure to Retool or similar low-code tools for operational write-back workflows (nice to have)
- FastAPI or similar Python API frameworks (Flask, Django REST) for serving data products as services (nice to have)
Benefits:
- 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
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