Senior Software Engineer

About the role

You will own the full lifecycle for cancer data features, designing secure flows that transform hospital records into worldwide evidence while guiding global teams with clarity and care. This role demands a calm problem-solver who builds lasting solutions and questions every assumption in the status quo. You will be the technical authority for your area of responsibility, ensuring that strategic goals are translated into robust, scalable technology. You will partner closely with data scientists and product managers to translate complex oncology requirements into resilient software components. This position requires a disciplined engineer who writes maintainable code and proactively identifies risks before they impact customers. You will act as a mentor within the Tokyo engineering organization, elevating the technical practice through code reviews and shared best practices.

Key facts

The position is located in our Tokyo office. It is a full-time, fixed-term contract with a duration of twelve months. The target annual compensation for this role is four million five hundred thousand Japanese Yen.

What you will do

You will architect intake pipelines that validate raw medical records before any downstream processing begins. You will design and build extraction workflows that enable reliable data movement between hospital systems and our platforms. During design review sessions, you will challenge proposed solutions to ensure security and privacy rules remain intact prior to implementation. You will handle hands-on deployment of solutions within hospital environments, adapting to strict network and infrastructure limitations. You will guide partner integrations, aligning product expectations with engineering constraints across global oncology teams. You will champion data modeling standards that shape schemas supporting long-term evidence generation and product evolution. You will drive quality assurance routines that catch issues early, reducing risk for clinical customers and internal stakeholders. You will establish clear documentation for each workflow stage, helping new engineers ramp quickly and work independently. You will implement monitoring strategies to detect anomalies in data pipelines and ensure timely resolution of incidents. You will collaborate with security teams to validate that data handling practices meet regulatory and compliance standards.

Requirements

You must bring five or more years of experience writing software in languages such as Java, C Sharp, or Python. You must demonstrate five or more years working with web technologies and backend frameworks such as those used for enterprise web applications. You must show three or more years managing relational databases like PostgreSQL or MySQL. You must prove three or more years performing Linux system administration in production-like settings. You must have direct experience with infrastructure as code approaches and cloud service patterns. You must offer deep system architecture knowledge, data modeling skills, and secure API design experience. You must use business-level English to communicate requirements and tradeoffs clearly. You must possess native or advanced business-level Japanese for professional discussions with clinicians and executives. You must understand networking fundamentals and troubleshoot issues in tightly restricted environments. You must accept travel to client sites for server operations and hands-on support when required. You must be comfortable working in a regulated industry where accuracy, auditability, and attention to detail are critical. You must demonstrate ownership of delivery timelines and accountability for production reliability.

Nice to have

Prior experience supporting EHR systems or clinical department platforms is valued. Experience with hands-on server hardware management and deployment activities is beneficial. Background deploying services on AWS infrastructure is a plus.

Practical notes

Please What you'll do

Flatiron Health builds technology that turns cancer data into practical insight. Teams work with real-world evidence and machine learning to support clinical decisions and research workflows.

The focus is on improving outcomes for people with cancer and enabling discoveries across the care journey. You help refine tools used by clinicians and researchers, contributing to clearer understanding and better care in oncology.