9amHealth
healthcare
SeniorDataAnalyst
“Senior Data Analyst at 9amHealth. Skills: Looker, LookML, SQL, Python, AI tools. 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”
What You'll Achieve.
Ensure that the clients we serve (large employers and health plans) receive best-in-class reporting; Strengthen client relationships; Improve our reporting, analysis, and client deliverables; Deliver insights that strengthen client relationships; Ensure accuracy, consistency, and timeliness of client-facing reporting
Industry & Context.
Translate business questions into analytical frameworks; Proactively explore data to surface trends, anomalies, and opportunities; Form hypotheses; Dig into data without being asked
What They're Looking For.
Must Have
5+ years of professional experience in a data analyst, analytics engineer, or BI-focused role, Deep expertise in Looker, including 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, Python skills for data analysis, scripting, and automation, Proficiency with AI-assisted development and analytics tools (e.g., Claude, ChatGPT, GitHub Copilot, Cursor), Experience building and delivering recurring client or stakeholder reports (e.g., QBRs, executive dashboards, performance reviews), Excellent communication and presentation skills
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
What You'll Do.
Own client-facing analytics: build
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
and dashboards in Looker
Write complex SQL queries across Redshift
and Athena to extract
and analyze data at scale
Develop Python scripts and notebooks for data wrangling
and analytical workflows
Leverage AI tools (e. g.
Cursor) in day-to-day analytics work
Identify and champion AI-powered use cases within the analytics workflow
Proactively explore data to surface trends
and present findings with clear business context and actionable recommendations
Define and monitor data quality metrics for client-facing reporting
Collaborate with the Data Engineering team to define data model requirements
validate pipeline outputs
and improve the analytical data layer
Document reporting logic
and analytical methodologies
Contribute to the evolution of our BI strategy
How You'll Work.
Team & Collaboration
Partner closely with the Customer Success team; Collaborate with the Data Engineering team; Knowledge sharing across teams
Communication Scope
Excellent communication and presentation skills; Ability to tailor the depth and framing of analysis to different audiences (Customer Success, clients, leadership)
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