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Bestow is a vertical technology platform serving major life insurers, modernizing the industry through AI-powered infrastructure that enables carriers to launch products in weeks instead of years. The Analytics team creates data solutions across the company, working cross-functionally to deliver curated data products, BI solutions, and high-value deliverables for both external partners and internal stakeholders.
In this role, you will span engineering and insights to improve automation and decision-making. You'll use SQL, dbt, CI/CD, and Google Cloud to automate data transformation pipelines flowing to enterprise partners. You'll create intuitive data visualizations using tools like Tableau to help partners understand their business and trust their data. You'll build subject matter expertise in the insurance domain to anticipate partner needs and recommend data governance best practices to improve data quality and controls.
Key responsibilities include constructing data validation checks and automated unit tests to catch quality issues early, collaborating with other data analysts and engineers, ensuring data quality through automated monitoring and alerting (including occasional on-call rotation), and maintaining clear documentation of designs and code changes. You'll be a strong communicator who contributes actively in stakeholder meetings, asks clarifying questions, and helps foster team growth and development through shared ownership and code review.
Bestow is backed by leading investors including Goldman Sachs, Hedosophia, NEA, Valar, and 8VC, and is trusted by major insurance carriers. The company offers flexible remote/hybrid work, meaningful benefits, equity, and substantial growth opportunities. The team values precision, purpose, and heart in reimagining a centuries-old industry.
REQUIREMENTS:
- 5+ years of experience
- Strong SQL skills (e.g., BigQuery) with ability to perform complex, effective, and efficient querying from cloud data warehouses
- Strong understanding of data transformation and quality engineering (e.g., dbt and Airflow)
- General software development lifecycle knowledge (SDLC, Agile development, CI/CD, Github)
- Strong understanding of data organization, data modeling, and schema design
- Track record of writing efficient queries and reducing compute costs
- Ability to communicate about data and findings through compelling summaries and clear visualizations (slides, whitepapers, Jupyter notebooks, Tableau, Google DataStudio, PowerBI)
- Demonstrated experience with AI coding assistants within IDEs or agentic CLIs
- Ability to create clear documentation through Github, Lucid, Jira, or Confluence
- Passionate about solving problems with data and delivering valuable results
