Marketing Analytics Lead: Data-Driven Growth

Nourish; New York (NY); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Nourish is a data-driven, AI-native digital health company scaling rapidly in the U.S. We’re hiring a Marketing Analytics Lead to own attribution, performance measurement, and channel optimization as the data-first backbone of growth.

You will build scalable data models, dashboards, and insights, collaborating with Marketing, Operations, Engineering, and Product to drive Nourish’s mission to improve health outcomes at scale.

Qualifications

• Have 5+ years of relevant experience owning analytics end to end at a fast-paced, high-growth company.
• Deep domain expertise in analytics engineering: you write clean SQL, know dbt and Fivetran, and understand data modeling and ETLs.
• You translate complex data into actionable insights and guide cross-functional decisions with clarity.
• You design scalable, end-to-end analytics systems and own the data foundation.

Responsibilities

• Own the full analytics stack for a business-critical function—from raw data to models, dashboards, and insights.
• Deliver high-impact insights by partnering with stakeholders to drive growth and efficiency.
• Build dashboards that enable fast, informed decision making across teams.
• Collaborate with Engineering to validate and optimize data pipelines for a trusted single source of truth.
• Lead by example in a data-first culture and document insights for broad consumption.

Skills

Analytics ownership

SQL

Analytics engineering

Data modeling

ETL pipelines

Tools

dbt

Fivetran

Airflow

Job description

Nourish is a data-driven, AI-native digital health company scaling rapidly in the U.S. We’re hiring a Marketing Analytics Lead to own attribution, performance measurement, and channel optimization as the data-first backbone of growth.

You will build scalable data models, dashboards, and insights, collaborating with Marketing, Operations, Engineering, and Product to drive Nourish’s mission to improve health outcomes at scale.