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

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)

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

Data Analytics Engineer II

Key skills