# Data Engineering Manager at Imagen

- Company: Imagen
- What the company does: AI-enabled subspecialist radiology for health systems. 99.5% service adherence, <1% addendum rate, 98% retention. Improve turnaround and diagnostic quality. Backed by GV.
- Company website: https://imagen.ai
- Type: Startups (AI role)
- Level: Senior
- Location: New York, United States
- Work setup: On-site
- Pay: $200K to $250K base salary per year (USD)
- Posted: 2026-09-10
- Apply by: 2026-10-25
- Apply: https://jobs.gem.com/imagen-technologies/am9icG9zdDoULDQ-L0du3Etu0gc4liQP
- Page: https://www.1752.vc/careers/jobs/imagen-data-engineering-manager/

## About the role

We’re looking for an experienced Engineering Manager to build and lead our AI Data Platform team. This platform is the backbone of our AI development, which has resulted in 6 FDA-cleared AI products aimed at reducing turnaround times and diagnostic error rates. This is an opportunity to build a team and a platform at a company where your work has a direct, measurable impact on patient outcomes by driving the development of Imagen's next generation of diagnostic tools.

## What they're looking for

- Mission-driven and passionate about building foundational technology to improve healthcare
- 8+ years of experience in software or data engineering, with at least 2 years in an engineering management role and a proven track record of building engineering teams or scaling teams through a significant growth phase
- Strong technical foundation in data engineering - comfortable reviewing system designs, making architectural decisions, and contributing code in Python and SQL when needed
- Experience with cloud-native data platforms and modern data infrastructure (e.g., data lakes, data warehouses, ETL/ELT pipelines, workflow orchestration tools like Airflow/Prefect/Dagster)
- Demonstrated ability to manage cross-functional stakeholders and translate business needs into engineering priorities
- Experience operating in a fast-paced, high-growth environment where priorities shift and ambiguity is the norm