Senior Analytics Engineer
Explicitly encourages use of AI coding assistants and accepts "vibe coding" with Python; heavy focus on semantic layers and AI/LLM interfaces for rapid analytics and tooling.
About the Role
Senior Analytics Engineer to own one or more business domains and build end-to-end analytics solutions using a modern data stack; deliver reliable pipelines, dbt models, semantic layer definitions, and AI-enabled intelligence to power reporting and LLM interfaces. Hybrid role based in Louisville, KY, collaborating closely with the CDO and a small analytics team with a path to leadership.
Job Description
Role
Senior Analytics Engineer reporting to the Chief Data Officer. Own one or more business domains end-to-end—responsible for data quality, pipeline reliability, modeling, governance, and delivering analytics and AI-driven insights that move the business.
Key Responsibilities
- Own domain data: quality, governance, monitoring, and reliability
- Build and maintain dbt models to transform raw data from Salesforce, NetSuite, DTCC, and internal systems into business-ready datasets
- Design and implement semantic layer definitions (metrics, dimensions, entities) for BI tools and AI/LLM interfaces
- Implement tests, monitoring, and alerting to catch data issues proactively
- Partner directly with business stakeholders to translate problems into analytics solutions
- Leverage AI coding assistants (e.g., GitHub Copilot, Claude, dbt Copilot) throughout the development lifecycle
- Contribute to shared infrastructure: pipeline orchestration, CI/CD, observability, and governance
- Develop data products such as AI-powered document processing, self-service analytics, or embedded partner BI
Requirements
- 5+ years in analytics engineering, data engineering, or a related field
- Expert SQL skills with ability to write and optimize complex queries
- Strong experience with dbt (modeling patterns, testing framework, deployment workflows)
- Experience with Snowflake or comparable cloud data warehouses (BigQuery, Redshift, Databricks)
- Proficiency with Python for data processing, automation, or analysis
- Working knowledge of Git and CI/CD practices for analytics code
- Demonstrated experience using or willingness to adopt AI coding assistants
- Ability to work onsite in Louisville, KY 3-5 days per week (relocation assistance available)
Nice to Have
- Experience in insurance, financial services, or annuities distribution
- Experience with semantic layer tools (dbt Semantic Layer, MetricFlow, Cube, AtScale, Snowflake Semantic Views)
- Familiarity with Salesforce data models and integration patterns
- Experience with modern BI tools (Sigma Computing, Hex, Lightdash)
- Background building AI/ML-powered data products or preparing data for LLM applications (Snowflake Intelligence, Streamlit)
- Pipeline orchestration experience (Airflow, Dagster, Prefect, Matillion, Fivetran, OpenFlow)
- Experience at an enterprise software company or SaaS platform
Success Metrics (30/60/90 Days)
- 30 Days: Onboarded to tech stack, understand data sources and models, shipped first code contribution
- 60 Days: Taken ownership of a domain, identified gaps/opportunities, created improvement roadmap, building stakeholder relationships
- 90 Days: Operating independently within domain, delivering measurable value, contributing to infrastructure decisions, recognized by stakeholders as go-to partner
Compensation & Benefits
- Competitive salary commensurate with experience
- Comprehensive health, dental, and vision insurance
- 401(k) with company match
- Relocation assistance available
- Professional development budget
Location & Working Conditions
- Louisville, KY (Hybrid, 3-5 days/week)
- Full-time role with potential path to leadership
- Typical office ergonomics and occasional light lifting (up to 25 lbs)