Senior Data Analyst

Role overview

As a Senior Data Analyst (senior individual contributor), you will own analytics and reporting for a line of business starting with Long-Term Care Insurance (LTCI). You will be the trusted source for getting the numbers right, producing partner reports and invoices, and evolving reporting toward analysis and recommendations.

Responsibilities

• Own recurring partner reporting and invoices for the business line (initially LTCI and its partner book), ensuring they are accurate and delivered on time each close.
• Rebuild reporting on dbt, moving logic out of manual/bespoke SQL and BI-tool calculated fields into tested, traceable, version-controlled models (dbt-first).
• Build and maintain internal data products such as dashboards, BI tools, and self-serve reporting; retire legacy reporting as you migrate.
• Write and maintain clean, tested SQL in BigQuery, and ship changes via a Git branch + PR + review + merge workflow.
• Build and monitor scheduled data pipelines (e.g., Airflow DAGs) so reporting runs without manual intervention; surface exceptions via alerts.
• Partner directly with business and operations leaders to deliver analysis that changes decisions.
• Handle protected health information (PHI) with strong attention to data governance and accuracy.
• Use AI tooling as a genuine multiplier in daily work.

Requirements

• Experience owning recurring invoices and partner reporting for a business line, delivering accurately and on time.
• Strong dbt experience rebuilding reporting into tested, governed models with version control.
• Strong SQL skills and experience working with BigQuery.
• Experience with Git-based workflows (branches/PRs).
• Experience building/operating scheduled pipelines (e.g., Airflow DAGs) with alerting for exceptions.
• Ability to understand end-to-end data flow (source systems to outputs) and maintain high standards for timeliness and accuracy.
• Ability to work with healthcare data/PHI and treat governance as core.

Nice-to-haves

• Increasingly shift from reporting what happened to analyzing why and recommending what to do next.
• Comfort applying AI tooling in a first-class way to improve productivity and analysis quality.