AI-Native Data Analytics Lead

Garner Health

New York (NY)

On-site

USD 167,000 - 210,000

Full time

14 days+

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Benefits offered by this job

Equity incentive
Flexible PTO
Health/Dental/Vision plans
401(k)

Job summary

Garner Health in New York City is seeking an AI‑Native Data Analyst to turn fuzzy questions into reliable metrics, dashboards, and analyses. You will own analytics end‑to‑end and partner with stakeholders to define success across products and operations.

Grow deep domain expertise, build scalable data pipelines, and improve reporting coverage while advocating best data practices and automation.

Qualifications

  • 5+ years of experience in Data Analytics, BI, or similar data-centric role.
  • Ability to translate ambiguous business questions into data-driven solutions.
  • Autonomy and ownership of reporting projects end-to-end.
  • Automation mindset with a bias toward scalable, repeatable work.
  • Comfort with AI-enabled analytics and dashboards.
  • Experience enabling self-serve access to information.
  • Experience with a BI/visualization tool is helpful.
  • Hands-on with Snowflake and SQL at scale; dbt preferred.

Responsibilities

  • Own KPIs and dashboards end-to-end across business domains.
  • Be a thought partner on measurement with stakeholders.
  • Build scalable data pipelines with data engineering.
  • Develop deep domain expertise to drive insights.
  • Close reporting gaps with new dashboards and insights.
  • Raise data-practice standards in visualization and documentation.
  • Answer high-stakes, ambiguous questions with deep-dives.

Skills

Data Analytics
Business Intelligence
Cross-functional translation
Automation mindset
AI Nativity
Self-serve access
SQL
Snowflake
dbt
Looker
Tableau
Power BI

Tools

Snowflake
SQL
dbt
Looker
Tableau
Power BI

Job description

Garner Health in New York City is seeking an AI‑Native Data Analyst to turn fuzzy questions into reliable metrics, dashboards, and analyses. You will own analytics end‑to‑end and partner with stakeholders to define success across products and operations.

Grow deep domain expertise, build scalable data pipelines, and improve reporting coverage while advocating best data practices and automation.

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