About the job
About Hone
Hone is revolutionizing healthcare with our innovative online medical clinic that focuses on enhancing longevity and empowering individuals to take charge of their health. By leveraging advanced scientific research, we help both men and women unlock their full potential. Our team is at the core of our mission, driving our success through our commitment to our brand values:
- Champion Patient Needs
- Execute Relentlessly
- Communicate Constructively
- Collaborate Generously
- Turn Obstacles Into Opportunity
- Give With Gratitude
As a fully virtual organization since our inception, Hone continues to embrace a remote-first culture.
Our Ideal Candidate
We are seeking a mission-driven Senior Data Engineer who is a proactive multi-tasker dedicated to making a meaningful impact. The ideal candidate thrives in a dynamic, fast-paced environment and is eager to tackle challenges with enthusiasm. They possess a strong collaborative spirit and excel in both independent and team-oriented tasks, fostering open communication. With a commitment to learning and development, they exhibit humble leadership while driving initiatives to help others live longer, healthier lives.
The Role
As a Senior Data Engineer at Hone, you will report directly to the Senior Director of Data, Analytics, and Machine Learning. Your primary responsibility will be to develop and maintain the pipelines and infrastructure that facilitate analytics, reporting, and machine learning projects. Additionally, you will play a key role in constructing a longevity ontology knowledge graph. This position is perfect for someone with over 5 years of experience looking to expand their influence and technical expertise within a collaborative team.
Primary Responsibilities
Your key responsibilities will include (but are not limited to):
- Developing, maintaining, and optimizing reliable data pipelines using SQL, dbt, and Python.
- Building and managing an ontology graph database with CosmosDB and Gremlin.
- Leveraging agentic AI to streamline and automate pipeline development.
- Working alongside Analytics Engineers, Data Scientists, Analysts, and Software Engineers to transform and structure data to fulfill business objectives.

