Analytics Engineer

About the role

ABOUT HIPP

Hipp is an AI-native healthcare platform built to modernize operations for non-hospital healthcare providers. We partner closely with ABA, behavioral health, and therapy organizations to streamline clinical workflows, billing, and revenue cycle operations — so providers can focus on delivering care.

Our platform combines EMR, billing infrastructure, and operational workflows with AI-driven automation, helping providers run more efficient practices and improve patient outcomes.

We’re building the next generation of healthcare infrastructure and are looking for thoughtful, product-minded engineers who want to build real systems, move quickly, and take ownership in a fast-moving startup environment.

Role Overview

We are seeking an experienced and highly motivated Analytics Engineer to join Hipp Health. This person will drive the creation, maintenance, and improvements of our entire data platform underlying our ML and AI efforts. They will also ideate, create, and refine the data modeling that our clients rely on every day to drive their operations and use to inform their strategic decisions. This role requires a strong background in data visualization, SQL, and data analysis. This person will collaborate with Product Managers and Data Scientists to architect scalable schemas and maintain high standards for warehouse integrity and precision. Experience within the health sector is a significant advantage.

Key Responsibilities

- Contribute to the continuous improvement of our data infrastructure and BI processes.

- Drive the continued evolution and optimization of our analytics data platform.

- Develop, maintain, and manage dynamic dashboards and reports using data visualization tools.

- Write complex SQL queries to extract, manipulate, and analyze data from various sources.

- Perform in-depth data analysis to identify trends, patterns, and root causes, and present findings clearly to stakeholders.

- Collaborate with cross-functional teams to understand business requirements and translate them into technical specifications.

- Monitor data quality and integrity, ensuring accuracy and reliability of reports.

- Product analytics: understand, analyze usage and use insights to drive data-driven product strategy

REQUIRED QUALIFICATIONS

Experience

- Minimum of 3+ years of professional experience in Analytics Engineering, Data Engineering, or Data Analytics, with a focus on building production-ready data pipelines and models.

Technical Skills

- Data Pipelines: Experience with building and maintaining data warehouses for ETL, operational analyses, stakeholder reporting, etc.

- Data Engineering: Experience with orchestration layer (e.g., Airflow, Prefect), data governance, OLAP database, schema design, query optimization

- Proficiency with Git workflows (branching, pull requests, code reviews) to manage data transformation code.