Lead Analytics Engineer — AI-Driven Health Data

Develop Health; Menlo Park (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health insurance

Equity

Flexible PTO

Equipment budget

Job summary

Develop Health in Menlo Park seeks a Lead Analytics Engineer to own analytics and shape our AI-first data platform. You will reinvent how providers, pharmacies, and payers access insights, diagnose bottlenecks, and drive faster patient outcomes.

You'll strengthen dbt and Snowflake foundations, define trusted metrics, and build analytics agents and self-service workflows. This hands-on role reports to the data leadership and requires strong SQL, dbt, and cloud data warehouse experience.

Qualifications

• 3+ years of hands-on analytics or data engineering experience with deep SQL/dbt skills.
• Experience with Snowflake or other modern cloud data warehouse.
• Ability to turn ambiguous questions into actionable analyses and data products.
• Familiarity with building or using AI-native analytics and agents.

Responsibilities

• Work directly with Product, Operations, Engineering, Finance, and Go-to-Market leaders to identify decisions where better data can modify outcomes and own those problems through adoption.
• Strengthen dbt and Snowflake foundations and establish trusted metrics for patient access, automation, and performance.
• Advance our customer-facing analytics product so customers can understand performance and bottlenecks and take action.
• Build governed analytics agents, reusable skills, and self-service workflows across the company.

Skills

SQL

dbt

Snowflake

Analytics

Problem ownership

Communication

AI-native analytics

Tools

Grafana

Hex

Looker

Mode

Python

Orchestration systems

Job description

Develop Health in Menlo Park seeks a Lead Analytics Engineer to own analytics and shape our AI-first data platform. You will reinvent how providers, pharmacies, and payers access insights, diagnose bottlenecks, and drive faster patient outcomes.

You'll strengthen dbt and Snowflake foundations, define trusted metrics, and build analytics agents and self-service workflows. This hands-on role reports to the data leadership and requires strong SQL, dbt, and cloud data warehouse experience.