Staff Analytics Engineer - Remote AI-Ready Data Platform

53 Stations; United States; On-site; USD 140,000 - 180,000; Full time

Job summary

Function Health is seeking a Staff Analytics Engineer to own the semantic layer at the core of our data platform. You will shape trusted data models and metrics that power dashboards, self-serve analytics, and AI-driven data agents.

You will collaborate with data scientists, product engineers, and business leaders to ensure accurate answers to any data question, while maintaining governance and high data quality in a fully remote team across the US.

Qualifications

• 8+ years analytics/data engineering experience with staff-level impact.
• Deep SQL and Python expertise.
• Strong data modeling fundamentals with well-documented models; dbt is a plus.
• Experience with modern data stack tools (Databricks, Snowflake/BigQuery, Airflow).
• Proven track record of resilient, production-grade data systems.

Responsibilities

• Own the semantic layer with metrics, dimensions, and data models as the source of truth.
• Architect for AI-readiness to power AI-driven analytics agents with clean schemas and data contracts.
• Drive data quality through observability, testing, and alerting across pipelines.
• Enable self-serve analytics by delivering tooling and dashboards for product, clinical, and business teams.
• Set standards for data modeling conventions, documentation, and code reviews across the data org.
• Collaborate cross-functionally to translate business questions into data solutions and improve event logging and measurement.

Skills

Advanced SQL

Python

Data Modeling

dbt

Databricks

Snowflake/BigQuery

BI Tools

Tools

Databricks

Snowflake

BigQuery

Airflow

Looker/Tableau

Unity Catalog

Job description

Function Health is seeking a Staff Analytics Engineer to own the semantic layer at the core of our data platform. You will shape trusted data models and metrics that power dashboards, self-serve analytics, and AI-driven data agents.

You will collaborate with data scientists, product engineers, and business leaders to ensure accurate answers to any data question, while maintaining governance and high data quality in a fully remote team across the US.