Senior Data Analyst, Customer Success

We are looking for a Data Analyst to join our Data & Analytics team and become the analytics partner to our Customer Success organization. Your primary mission: ensure that the clients we serve (large employers and health plans) receive best-in-class reporting, from recurring Quarterly Business Reviews to ad hoc analyses that answer the questions they care about most.

Responsibilities

Own client-facing analytics: build, maintain, and continuously improve the dashboards and reports used in Quarterly Business Reviews and ad hoc client requests; Partner closely with the Customer Success team to understand client needs, translate business questions into analytical frameworks, and deliver insights that strengthen client relationships; Design and build production-quality LookML models, explores, and dashboards in Looker, serving as the team's Looker subject matter expert; Write complex SQL queries across Redshift, Aurora/MySQL, and Athena to extract, transform, and analyze data at scale; Develop Python scripts and notebooks for data wrangling, automated reporting, and analytical workflows that go beyond what SQL alone can do; Leverage AI tools (e.g., Claude, GitHub Copilot, Cursor) in day-to-day analytics work to accelerate query development, code generation, data exploration, and documentation; Identify and champion AI-powered use cases within the analytics workflow, such as automated anomaly detection, natural-language data summarization, predictive insights for client reporting, or AI-assisted QBR narrative generation; Proactively explore data to surface trends, anomalies, and opportunities, and present findings with clear business context and actionable recommendations; Define and monitor data quality metrics for client-facing reporting, ensuring accuracy, consistency, and timeliness; Collaborate with the Data Engineering team to define data model requirements, validate pipeline outputs, and improve the analytical data layer; Document reporting logic, data definitions, and analytical methodologies to enable self-service and knowledge sharing across teams; Contribute to the evolution of our BI strategy, including dashboard governance, naming conventions, and version control practices for LookML.

Requirements

5+ years of professional experience in a data analyst, analytics engineer, or BI-focused role; Deep expertise in Looker, including strong command of LookML: building and maintaining models, views, explores, derived tables, and parameterized dashboards; Expert-level SQL: complex joins, window functions, CTEs, subqueries, and query performance tuning; Strong Python skills for data analysis, scripting, and automation; Proficiency with AI-assisted development and analytics tools (e.g., Claude, ChatGPT, GitHub Copilot, Cursor); Strong appetite for integrating AI into analytics workflows; Self-starter mentality: you proactively identify problems, dig into data without being asked, form hypotheses, and bring insights to stakeholders with actionable recommendations; Strong business acumen and the ability to understand the "so what" behind the numbers; Experience building and delivering recurring client or stakeholder reports (e.g., QBRs, executive dashboards, performance reviews); Excellent communication and presentation skills, with the ability to tailor the depth and framing of analysis to different audiences (Customer Success, clients, leadership); Familiarity with cloud data warehouses (Redshift preferred) and data lake concepts (S3, Parquet)

Nice to have

Experience in health tech, digital health, or healthcare services, including familiarity with healthcare-specific data (claims, clinical, eligibility, pharmacy, outcomes measurement); Hands-on experience building or deploying AI-powered analytics features, such as automated reporting narratives, anomaly detection, classification models, or LLM-based data summarization; Familiarity with AWS data services (Glue, Athena, S3, CloudWatch); Experience with event-based analytics platforms such as Mixpanel or Amplitude; Exposure to dbt or similar analytics engineering tools for managing transformation logic; Familiarity with version control (Git) for LookML and analytical code; Prior experience working closely with Customer Success, Account Management, or client-facing teams; Background in a startup or high-growth environment where you wore multiple hats and owned outcomes end to end.

Benefits

health, dental, and vision insurance; flexible PTO; work from home options; professional development budget; support for continuing education; opportunity to make a meaningful impact on chronic disease management and patient outcomes; collaborative, mission driven culture focused on improving healthcare accessibility and affordability