Senior Data Engineer - Oncology Data Platform (Hybrid)

Doist; New York (NY); Hybrid; USD 120,000 - 190,000; Full time

Benefits offered by this job

Flexible hours

Paid time off

401(k)

Job summary

Flatiron Health is seeking a Senior Data Engineer to design, build, and maintain data solutions that empower oncology research and customer insights. You will mentor engineers and shape data pipelines across AWS, Snowflake, and Python-based tools.

In a hybrid role, you’ll collaborate with clinical analysts and product teams to translate research needs into scalable data systems while maintaining data quality and governance.

Qualifications

• 4+ years in data engineering or data-intensive apps
• Strong SQL and Python proficiency
• Experience building and maintaining ETL/ELT pipelines and orchestration
• Experience with AWS and Snowflake
• Experience leading data engineering teams
• Ability to collaborate with non-technical stakeholders
• Healthcare data experience bonus

Responsibilities

• Design, build, and maintain data solutions delivering insights for customers and R&D
• Collaborate with clinical data analysts to ensure data quality and compliance
• Break down requirements into actionable work and surface risks early
• Translate needs into technical solutions, balancing constraints and timelines
• Mentor and develop junior data engineers
• Manage multiple pipelines and stakeholder expectations for on-time delivery
• Participate in design and code reviews to elevate team quality
• Identify inefficiencies and propose improvements
• Leverage AI-assisted coding tools while maintaining quality
• Monitor CI/CD pipelines and troubleshoot root causes

Skills

SQL

Python

ETL/ELT

AWS

Snowflake

Data modeling

Leadership

Git

Documentation

CI/CD

Education

Bachelor's in CS/Data Science

Tools

Airflow

Docker

Job description

Flatiron Health is seeking a Senior Data Engineer to design, build, and maintain data solutions that empower oncology research and customer insights. You will mentor engineers and shape data pipelines across AWS, Snowflake, and Python-based tools.

In a hybrid role, you’ll collaborate with clinical analysts and product teams to translate research needs into scalable data systems while maintaining data quality and governance.