Senior Analytics Engineer

YOUR ROLE

We're seeking a Senior Analytics Engineer to help shape the future of data-driven decision making at our rapidly growing, insurance technology company. As a key member of our data team, you'll architect and implement analytics solutions that power both strategic insights and operational workflows. You'll work at the intersection of our modern data stack and business operations — building robust data models, designing self-service data applications, and leading the migration from our legacy Redshift and Tableau environment to our modern stack.

This role offers a unique opportunity to work with cutting-edge tools (dbt, Snowflake, Sigma, Hex, Claude) while having significant influence on our data strategy and technical architecture. You'll collaborate closely with business teams to transform complex data into actionable insights, self-service analytics, and AI-powered applications.

What You'll Do

• Design, build, and maintain data models using dbt core, ensuring efficient, scalable, and well-documented analytics solutions
• Lead and execute the migration of data assets from Redshift and Tableau to our modern stack — Snowflake, Sigma, and Hex — ensuring data quality and business continuity throughout
• Build interactive data applications, dashboards, and reports in Sigma and Hex that enable self-service analytics for business stakeholders
• Design, build, and govern our centralized semantic layer to standardize business metrics and enable true self-service analytics across Sigma and Hex
• Develop and maintain Python scripts for analytics automation, predictive models, and operational reporting
• Implement and maintain data quality testing frameworks to ensure reliable, trustworthy data
• Integrate AI and LLM capabilities (including Claude) into analytics workflows to automate data enrichment, text analysis, and predictive modeling for insurance use cases
• Create and manage JIRA epics, stories, and tasks to track development work
• Collaborate with stakeholders to understand business requirements and translate them into technical solutions
• Additional duties and responsibilities as assigned.

• 5+ years of experience in analytics engineering or a similar technical role
• Expert-level SQL skills with deep understanding of data warehouse concepts
• Hands-on experience with dbt for data transformation and modeling — dbt core experience preferred
• Proficiency building data applications, dashboards, and reports in Sigma and/or Hex
• Proven experience leading or executing a migration from a legacy data warehouse (Redshift) or BI tool (Tableau) to a modern analytics stack
• Expert-level experience with Snowflake as a cloud data warehouse (required); familiarity with AWS Redshift a plus for migration context
• Proven experience building and maintaining a semantic layer / metrics catalog to serve multiple downstream applications
• Working knowledge of Python for analytics automation, predictive modeling, and reporting
• Experience with version control systems (Git) and CI/CD practices
• Practical experience leveraging AI/LLMs within a data stack to solve business problems — including prompt engineering, AI-assisted analytics, or GenAI tools in Hex, Sigma or Snowflake
• Experience with data lakehouse technologies, including Apache Iceberg and AWS Glue (a plus)
• Experience in commercial insurance, financial services, or venture-backed technology companies
• Track record of building data solutions in B2B SaaS or enterprise software companies
• Experience using JIRA for project management and tracking
• Excellent communication skills with high attention to detail
• Bachelor's degree in Computer Science, Engineering, Mathematics, or related field
• Self-starter who thrives in a fast-paced environment, capable of juggling multiple initiatives and meeting strict deadlines